1 Introduction

During this training session, we are going to use ChIP-seq and RNA-seq data from Laurette et al. (Laurette et al. 2015) which are available in GEO as GSE61967. Data have already been processed.

1.1 Processing of RNA-seq data

1.1.1 Preprocessing

Reads were preprocessed in order to remove adapter, polyA and low-quality sequences (Phred quality score below 20). After this preprocessing, reads shorter than 40 bases were discarded for further analysis. These preprocessing steps were performed using cutadapt (Martin 2011) version 1.10.

1.1.2 Mapping

Reads were mapped onto the hg38 assembly of Homo sapiens genome using STAR (Dobin et al. 2013) version 2.5.3a.

1.1.3 Quantification

Gene expression quantification was performed from uniquely aligned reads using htseq-count version 0.6.1.p1 (S. Anders, Pyl, and Huber 2015), with annotations from Ensembl version 103 and “union” mode. Only non-ambiguously assigned reads have been retained for further analyses.

1.1.4 Normalization

Read counts have been normalized across samples with the median-of-ratios method proposed by Anders and Huber (Anders and Huber 2010), to make these counts comparable between samples.

1.1.5 Differential expression analysis

Differential expressed genes between wild type ans shBRG1 cells was performed using the edgeR R package (Robinson, McCarthy, and Smyth 2010). We called significant changes when FDR < 0.01, absolute log fold change over 1 and minimum average log normalized count over 5.

1.2 Processing of ChIP-seq data

1.2.1 Mapping

Reads were mapped to Homo sapiens genome (assembly hg38) using Bowtie (Langmead et al. 2009) v1.0.0 with default parameters except for “-p 3 -m 1 –strata –best –chunkmbs 128”. The following table shows the number of reads aligned to the Homo sapiens genome.

(#tab:stats.chipseq)Mapping statistics of ChIP-seq data analyzed during this training session. Column “Raw reads” corresponds to the number of input reads. Column “Aligned reads” corresponds to the number of reads aligned exactly 1 time. Column “Multimapped” corresponds to the number of reads aligned > 1 times. Column “Unmapped” corresponds to the number of reads aligned 0 time.
Sample ID Sample name raw reads aligned reads multimapped reads unmapped reads
SRR1594290 MITF_CHIP-seq 84856252 54369181 (64.07%) 12823841 (15.11%) 17663230 (20.82%)
SRR1594291 SOX10_CHIP-seq 38202152 29594694 (77.47%) 6128890 (16.04%) 2478568 (6.49%)
SRR1594292 BRG1siCTRL_CHIP-seq 50190992 40134919 (79.96%) 6403809 (12.76%) 3652264 (7.28%)
SRR1594293 BRG1siMITF_CHIP-seq 64765675 44480241 (68.68%) 9357361 (14.45%) 10928073 (16.87%)
SRR1594294 GFPsiCTRL_CHIP-seq 38148419 26273410 (68.87%) 5722823 (15.00%) 6152186 (16.13%)
SRR1594295 MITF_Input 29433042 19970925 (67.85%) 4049711 (13.76%) 5412406 (18.39%)
SRR1594296 SOX10_Input 35449561 27381422 (77.24%) 7045192 (19.87%) 1022947 (2.89%)
SRR1596499 BRG1siSOX10_CHIP-seq 42745544 34418403 (80.52%) 6855741 (16.04%) 1471400 (3.44%)

1.2.2 Peak Calling

Prior to peak calling, reads falling into Encode blacklisted regions (“(2014) Mod/Mouse/humanENCODE: Blacklisted Genomic Regions for Functional Genomics Analysis - Anshul Kundaje” n.d.) were removed using bedtools intersect v2.26.0 (Quinlan and Hall 2010). Then peak calling was done with Macs2 v2.1.1 with default parameters.

Table 1.1: Number of peaks detected
IP sample Input sample No. of peaks
BRG1siCTRL_CHIP-seq GFPsiCTRL_CHIP-seq 72024
BRG1siMITF_CHIP-seq GFPsiCTRL_CHIP-seq 33984
BRG1siSOX10_CHIP-seq GFPsiCTRL_CHIP-seq 73267
MITF_CHIP-seq MITF_Input 9702
SOX10_CHIP-seq SOX10_Input 4538

1.2.3 Generation of BigWig files

Normalized BigWig files were generated using Homer (Heinz et al. 2010) makeUCSCfile v4.11.0 with the following parameter ‘-norm 1e7’ meaning that data were normalized to 10M reads.

1.3 Define the paths to the data

We create a list containing the absolute paths to the data we will use along the practice and their file names.

params <- list(
  chipseq= "/shared/projects/2315_ebaii_2/ChIPseq/data/ChIPseq/",
  mapping.chipseq= "stats_mappingChIPseq.tsv",
  peakcalling.chipseq="stats_peakCalling.tsv",
  brg1= "BRG1siCTRL_CHIP-seq_peaks.narrowPeak",
  mitf= "MITF_CHIP-seq_peaks.narrowPeak",
  sox10= "SOX10_CHIP-seq_peaks.narrowPeak",
  brg1.bw= "BRG1siCTRL_CHIP-seq.bw",
  mitf.bw= "MITF_CHIP-seq.bw",
  sox10.bw= "SOX10_CHIP-seq.bw",
  rnaseq= "/shared/projects/2315_ebaii_2/ChIPseq/data/RNAseq/RNAseq_diff_norm.RData"
  )

2 Description and statistics of BRG1 dataset

2.1 Load data

Peak files are in narrowPeak format which is of the form (source):

  1. chrom - Name of the chromosome (or contig, scaffold, etc.).
  2. chromStart - The starting position of the feature in the chromosome or scaffold. The first base in a chromosome is numbered 0.
  3. chromEnd - The ending position of the feature in the chromosome or scaffold. The chromEnd base is not included in the display of the feature. For example, the first 100 bases of a chromosome are defined as chromStart=0, chromEnd=100, and span the bases numbered 0-99.
  4. name - Name given to a region (preferably unique). Use “.” if no name is assigned.
  5. score - Indicates how dark the peak will be displayed in the browser (0-1000). If all scores were “‘0”’ when the data were submitted to the DCC, the DCC assigned scores 1-1000 based on signal value. Ideally the average signalValue per base spread is between 100-1000.
  6. strand - +/- to denote strand or orientation (whenever applicable). Use “.” if no orientation is assigned.
  7. signalValue - Measurement of overall (usually, average) enrichment for the region.
  8. pValue - Measurement of statistical significance (-log10). Use -1 if no pValue is assigned.
  9. qValue - Measurement of statistical significance using false discovery rate (-log10). Use -1 if no qValue is assigned.
  10. peak - Point-source called for this peak; 0-based offset from chromStart. Use -1 if no point-source called.
## The package ChIPseeker provides a function to load peak files such as narrowPeaks as GRanges objects
## Here BRG1 peak set is loaded into a list of peaks
## this list can be extended if there are more datasets
library(ChIPseeker)
peaks <- list()
peaks[["BRG1"]] <- readPeakFile(paste0(params$chipseq, params$brg1), as="GRanges")
peaks
## $BRG1
## GRanges object with 72024 ranges and 7 metadata columns:
##           seqnames            ranges strand |                     V4        V5
##              <Rle>         <IRanges>  <Rle> |            <character> <integer>
##       [1]     chr1     980402-981178      * | BRG1siCTRL_CHIP-seq_..        77
##       [2]     chr1     983476-984526      * | BRG1siCTRL_CHIP-seq_..       108
##       [3]     chr1   1000729-1001179      * | BRG1siCTRL_CHIP-seq_..        90
##       [4]     chr1   1001762-1002054      * | BRG1siCTRL_CHIP-seq_..        40
##       [5]     chr1   1020914-1021207      * | BRG1siCTRL_CHIP-seq_..       114
##       ...      ...               ...    ... .                    ...       ...
##   [72020]     chrY 18936757-18937116      * | BRG1siCTRL_CHIP-seq_..        37
##   [72021]     chrY 19577774-19578316      * | BRG1siCTRL_CHIP-seq_..        73
##   [72022]     chrY 19891214-19892094      * | BRG1siCTRL_CHIP-seq_..       114
##   [72023]     chrY 19892553-19893192      * | BRG1siCTRL_CHIP-seq_..        55
##   [72024]     chrY 21837647-21838039      * | BRG1siCTRL_CHIP-seq_..        55
##                    V6        V7        V8        V9       V10
##           <character> <numeric> <numeric> <numeric> <integer>
##       [1]           .   5.81321  10.22971   7.71662       166
##       [2]           .   5.97792  13.59661  10.83201       384
##       [3]           .   6.65677  11.62894   9.01201       199
##       [4]           .   3.78100   6.17367   4.02109       209
##       [5]           .   8.11634  14.29797  11.46427       158
##       ...         ...       ...       ...       ...       ...
##   [72020]           .   4.53175   5.93549   3.79936       167
##   [72021]           .   6.32404   9.87728   7.38650       165
##   [72022]           .   7.86030  14.29797  11.46427       711
##   [72023]           .   5.29987   7.83781   5.50942       390
##   [72024]           .   5.55592   7.83781   5.50942       152
##   -------
##   seqinfo: 24 sequences from an unspecified genome; no seqlengths

Peaks are stored as GenomicRanges objects; this is an R format which look like the bed format, but is optimized in terms of memory requirements and speed of execution.

We can start by computing some basic statistics on the peak sets.

2.2 How many peaks were called?

Compute the number of peaks per dataset. We use here a function from the apply family which help to apply recursively a given function on elements of the object. We will use these functions all along the course.

# sapply() function takes list, vector or data frame as input and gives output in vector or matrix
# sapply apply the same function (here length) to all elements
# of the list "peaks"
sapply(peaks,length)
##  BRG1 
## 72024

Make a simple barplot showing the number of BRG1 peaks.

Show code: barplot

 
barplot(sapply(peaks,length))

Let’s create a barplot with ggplot2 out of this data.
Step by step:
- Do not forget to load the ggplot2 library.

Show code: load ggplot2

 
# Load ggplot2 library
library(ggplot2)
  • Create a data.frame with two columns: IP contains names of the chipped TFs and NbPeaks contains the number of peaks.

Show code: create the data.frame

 
# create a table with the data to display
peak.lengths <- data.frame(IP=names(peaks),
                           NbPeaks=sapply(peaks,length))
  • use ggplot2 with the appropriate geometric object geom_*

Show code: barplot with ggplot2

 
# 
# make the barplot
ggplot(peak.lengths, aes(x=IP, y=NbPeaks)) +
         geom_col()

We can customize the plots by changing colors.

# Let's add colors to the barplot
# In R it exists some already defined colors palettes
# the most widely used palette is RColorBrewer.
# This R library offers several color palettes
# See:
library(RColorBrewer)
par(mar=c(3,4,2,2))
display.brewer.all()

Now lets add colors to the barplot.
Step by step:
- Add the new information fill=IP to let ggplot know that colors change based on chipped protein

Show code: color according to the chipped TF (column IP)

 
ggplot(peak.lengths, aes(x=IP, y=NbPeaks, fill=IP)) +
         geom_col()

We want to use colors from RColorBrewer library with the “Set1” color palette. To set your own colors to fill the plot, several functions are available (scale_fill_*), here we use scale_fill_brewer.

Show code: color according to the chipped TF (column IP) and set RColorBrewer palette to Set1

 
ggplot(peak.lengths, aes(x=IP, y=NbPeaks, fill=IP)) +
         geom_col()+
         scale_fill_brewer(palette="Set1")

2.3 How large are these peaks?

BRG1 peaks were loaded as a GRanges object.
- To manipulate it we load the library GenomicRanges - Use the appropriate function to retrieve the width of the peaks from the GRanges - Use a function to summarize the peak length (display the statistics (minimum, maximum, quartiles) of the distribution)

Show code: Display peak length statistics

 
## we use the function width() from GenomicRanges
library(GenomicRanges)
summary(width(peaks$BRG1))
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   254.0   308.0   427.0   578.7   671.0  9186.0
# or quantile(width(peaks$BRG1))

Create a simple boxplot of the peak sizes.

Show code: Display peak length statistics as a boxplot

 
peak.width <- lapply(peaks,width)
boxplot(peak.width)

Now, create a nice looking boxplot with ggplot2. ggplot takes a data frame as input. We can either create a date frame, this is what we have done when we created the barplot. Here, we are going to use the package reshape2 which, among all its features, can create a data frame from other types of data:

# Load the package
library(reshape2)
peak.width.table <- melt(peak.width)
head(peak.width.table)
##   value   L1
## 1   777 BRG1
## 2  1051 BRG1
## 3   451 BRG1
## 4   293 BRG1
## 5   294 BRG1
## 6   351 BRG1

Create a ggplot object with correct aesthetics to display a boxplot according the chipped TF (x-axis) and their width (y-axis). Then use appropriate geometric object geom_*.

Show code: Display peak length statistics with ggplot2

 
## create boxplot
ggplot(peak.width.table, aes(x=L1, y=value)) +
         geom_boxplot()

By default, the background color is grey and often does not allow to highlight properly the graphs. Many theme are available defining different graphics parameters, they are often added with a function theme_*(), the function theme() allows to tune your plot parameter by parameter. We propose here to use theme_classic() that changes a grey background to white background. Some peaks are very long and squeeze the distribution, one way to make the distribution easier to visualize is to transform the axis to log scale. Finally, we want to remove the x label, change the y label to ‘Peak sizes’ and the legend relative to the fill color from “L1” to “TF”.
Using the ggplot2 documentation (e.g. https://ggplot2.tidyverse.org/ or google it, try to enhance the boxplot.

Enhance it !

 
# - theme_classic() change grey background to white background
# - fill=L1 and scale_fill_brewer(palette="Set1") colors boxplots
# based on chipped protein and with colors from RColorBrewer Set1 palette
# - labs changes x and y axis labels and legend title
# - scale_y_log10() set y axis to a log scale so that we can have a nice
# view of the data in small values
ggplot(peak.width.table, aes(x=L1, y=value, fill=L1)) +
         geom_boxplot()+
         theme_classic()+
         scale_fill_brewer(palette="Set1")+
         labs(x = "", y = "Peak sizes", fill = "TF")+
         scale_y_log10()

2.4 Peak filtering

To make sure we keep only high quality data. We are going to select those peaks having a qValue >= 8. The qValue corresponds to the 9th column of narrowPeak files. So, we are going to set a threshold on this. How many peaks are selected ?

Show the code: select high quality peaks

 
## Select high quality peaks
peaks$BRG1 <- peaks$BRG1[peaks$BRG1$V9 >= 8]
## Compute the number of remaining peaks
length(peaks$BRG1)
## [1] 30874

2.5 Where are the peaks located over the whole genome?

Sometime, peaks may occur more in some chromosomes than others. We can display the genomic distribution of peaks along the chromosomes, using the covplot function from ChIPSeeker. Height of peaks is drawn based on the peak scores.

# genome wide BRG1 peak distribution
covplot(peaks$BRG1, weightCol="V5")

# chromosome wide BRG1 peak distribution
covplot(peaks$BRG1, chrs=c("chr1", "chr2"), weightCol="V5")

2.6 Functional annotation: genomic features enriched in BRG1 peaks

2.6.1 Generate annotation

We can assign peaks to the closest genes and genomic features (introns, exons, promoters, distal regions, etc…). We load ready-to-use annotation objects from Bioconductor: a OrgDB org.Hs.eg.db and a TxDB TxDb.Hsapiens.UCSC.hg38.knownGene objects.

## org.Hs.eg.db is an R object that contains mappings between Entrez Gene identifiers and GenBank accession numbers.
library(org.Hs.eg.db)
## Load transcript annotation
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene

This is done using the function annotatePeak which compares peak positions with the genomic feature positions of the reference genome. This function returns a complex object which contains all this information. As for the peaks coordinates, we store the peak annotations in a list that we first initialize as an empty list peakAnno <- list(). We define here the TSS regions as TSS positions -1000 bp +100 bp. Using the help of the function and annotation objects we have loaded, try to write the correct command line to annotate BRG1 peaks.

Show code: annotate BRG1 peaks

 
## Annotate peaks for all datasets and store it in a list
## Here TSS regions are regions -1000Kb/+100b arount TSS positions
## Peak annotations are stored in a list
peakAnno <- list()
peakAnno[["BRG1"]] = annotatePeak(peaks$BRG1, tssRegion=c(-1000, 100), TxDb=txdb, annoDb="org.Hs.eg.db")
## >> preparing features information...      2023-06-22 12:29:38 
## >> identifying nearest features...        2023-06-22 12:29:39 
## >> calculating distance from peak to TSS...   2023-06-22 12:29:40 
## >> assigning genomic annotation...        2023-06-22 12:29:40 
## >> adding gene annotation...          2023-06-22 12:29:59 
## >> assigning chromosome lengths           2023-06-22 12:29:59 
## >> done...                    2023-06-22 12:29:59
class(peakAnno$BRG1)
## [1] "csAnno"
## attr(,"package")
## [1] "ChIPseeker"
## Visualize and export annotation as a data table
# as.data.frame(peakAnno$BRG1)
head(as.data.frame(peakAnno$BRG1))
##   seqnames   start     end width strand                          V4  V5 V6
## 1     chr1  983476  984526  1051      *  BRG1siCTRL_CHIP-seq_peak_2 108  .
## 2     chr1 1000729 1001179   451      *  BRG1siCTRL_CHIP-seq_peak_3  90  .
## 3     chr1 1020914 1021207   294      *  BRG1siCTRL_CHIP-seq_peak_5 114  .
## 4     chr1 1069156 1070192  1037      * BRG1siCTRL_CHIP-seq_peak_10  96  .
## 5     chr1 1079517 1080087   571      * BRG1siCTRL_CHIP-seq_peak_11 179  .
## 6     chr1 1304853 1306013  1161      * BRG1siCTRL_CHIP-seq_peak_15 108  .
##        V7       V8       V9 V10
## 1 5.97792 13.59661 10.83201 384
## 2 6.65677 11.62894  9.01201 199
## 3 8.11634 14.29797 11.46427 158
## 4 6.90466 12.34852  9.65604 410
## 5 9.95583 21.25171 17.96153 213
## 6 5.97792 13.59661 10.83201 176
##                                          annotation geneChr geneStart geneEnd
## 1                                 Distal Intergenic       1    976121  982117
## 2                                          Promoter       1   1001138 1014540
## 3 Intron (ENST00000379370.7/375790, intron 1 of 35)       1   1020123 1056118
## 4 Exon (ENST00000412397.2/100288175, exon 10 of 10)       1   1070967 1074306
## 5                                 Distal Intergenic       1   1082146 1084072
## 6                                          Promoter       1   1292390 1305929
##   geneLength geneStrand geneId      transcriptId distanceToTSS         ENSEMBL
## 1       5997          2  84808 ENST00000694917.1         -1359 ENSG00000187642
## 2      13403          1   9636 ENST00000624697.4             0 ENSG00000187608
## 3      35996          1 375790 ENST00000620552.4           791 ENSG00000188157
## 4       3340          2 401934 ENST00000453464.3          4114 ENSG00000237330
## 5       1927          2  54991 ENST00000464905.1          3985 ENSG00000131591
## 6      13540          2 116983 ENST00000492936.5             0 ENSG00000131584
##     SYMBOL                                                 GENENAME
## 1    PERM1             PPARGC1 and ESRR induced regulator, muscle 1
## 2    ISG15                            ISG15 ubiquitin like modifier
## 3     AGRN                                                    agrin
## 4   RNF223                                  ring finger protein 223
## 5 C1orf159                      chromosome 1 open reading frame 159
## 6    ACAP3 ArfGAP with coiled-coil, ankyrin repeat and PH domains 3

All peak information contained in the peak list will be retained in the output of annotatePeak. Positions and strand information of nearest genes are reported. The distance from peak to the TSS of its nearest gene is also reported. The genomic region of the peak is reported in annotation column. Since some annotation may overlap, ChIPseeker adopted the following priority in genomic annotation :

  • Promoter
  • 5’ UTR
  • 3’ UTR
  • Exon
  • Intron
  • Downstream
  • Intergenic
  • Downstream is defined as the downstream of gene end.

This hierachy can be customized using the parameter genomicAnnotationPriority.

The annotatePeak function report(s) detail(led) information when the annotation is Exon or Intron(.) (F)or tion when the annotation is Exon or Intron, for instance “Exon (uc002sbe.3/9736, exon 69 of 80),” means that the peak is overlap(ing) with an Exon of transcript uc002sbe.3, (whose) corresponding Entrez gene ID is 9736 (Transcripts that belong to the same gene ID may differ in splice events), and this (contains/harbors).

The “annoDb” parameter is optional. If it is provided, some extra columns including SYMBOL, GENENAME, ENSEMBL/ENTREZID will be added.

–

Reminder: The TxDb class is a container for storing transcript annotations.

  • Bioconductor provides several packages containing TxDb objects for model organisms sur as Human and mouse. For instance, TxDb.Hsapiens.UCSC.hg38.knownGene, TxDb.Hsapiens.UCSC.hg19.knownGene for human genome hg38 and hg19, TxDb.Mmusculus.UCSC.mm10.knownGene and TxDb.Mmusculus.UCSC.mm9.knownGene for mouse genome mm10 and mm9, etc.

  • User can also prepare their own TxDb by retrieving information from UCSC Genome Bioinformatics and BioMart data resources by R function makeTxDbFromBiomart and makeTxDbFromUCSC.

  • One can also create a TxDb objects for his favourite organism using an annotation file in GTF/GFF format using the function makeTxDbFromGFF or the package GenomicFeatures.

Expand to find Coturnix japonica example

 
## download GTF file
download.file("https://ftp.ncbi.nlm.nih.gov/genomes/all/annotation_releases/93934/101/GCF_001577835.2_Coturnix_japonica_2.1/GCF_001577835.2_Coturnix_japonica_2.1_genomic.gtf.gz", "Coturnix_japonica_2.1.annotation.gtf.gz")
## Build TxDb object
library(GenomicFeatures)
txdb = makeTxDbFromGFF("Coturnix_japonica_2.1.annotation.gtf.gz")
## To save the txdb database
library(AnnotationDbi)
saveDb(txdb, 'txdb.Coturnix_japonica_2.1.sqlite')
## load it when needed
library(AnnotationDbi)
txdb = loadDb(file = 'txdb.Coturnix_japonica_2.1.sqlite')

–

2.6.2 Visualize genomic annotation

We can now perform a more detailed analysis of genomic features associated to our peaks (introns, exons, promoters, distal regions,…) visualizing the genomic distribution either as a pie chart with plotAnnoPie or as a bar chart plotAnnoBar.

Show code: Display peak distribution of genomic features

 
## distribution of genomic features for BRG1 peaks
# as a pie chart - which is the most widely used representation in publication
plotAnnoPie(peakAnno$BRG1)

# as a barplot
plotAnnoBar(peakAnno$BRG1)

However since some annotation overlap, ChIPseeker provides functions that help having a view of full annotation overlap.

library(UpSetR)
upsetplot(peakAnno$BRG1)
## Warning: Removed 133 rows containing non-finite values (`stat_count()`).

2.7 Heatmaps: visualisation of binding profiles

Heatmap(s) are widely used representation(s) of ChIP-seq data as they allow simultaneous visualization of read enrichment at various locations. For instance, one may want to represent reads related to a chipped protein in regions spanning +/-5Kb around all TSS of the reference genome. Another objective would be to compare read enrichment at the same locations in many chip-seq datasets.

2.7.1 BRG1 peak distribution

We want to know if BRG1 is binding large and/or narrow regions, unique and/or tandem etc.

First of all, for calculating the profile of ChIP peaks binding to the BRG1 center, we need to define peak centers and extend them each side. We will select the 10000 best q-value peaks (column V9) to lighten the matrix. Then (we need to) align the peaks that are mapped to these regions, and to generate the tagMatrix. The resulting matrix will be 2000*2+1 columns and 10000 lines which is quite big to display as a heatmap.

Step by step:
- Compute the center of BRG1 peaks using the GenomicRanges methods start and end. Assign the results to a new column in metadata of the BRG1 peaks object.

Show code: compute the peak centers

 
# Compute the center of the peaks and attribute it to a new
# column in the metadata of the BRG1 peak GRanges
peaks$BRG1$center.peak <- (start(peaks$BRG1) + end(peaks$BRG1))/2
  • Sort the peaks in decreasing order (column V9) and select the top 10,000.

Show code: order and select peaks

 
# For computation and memory efficiency reasons,
# we subset the top 10K peaks according to the FDR column (V9)
top.10000 <- peaks$BRG1[order(peaks$BRG1$V9,decreasing=T)][1:10000]
  • Create a GRanges object containing genomic positions of the 10K peak centers. You need to define seqnames and ranges in an IRanges object: IRanges(start,end).

Show code: Create GRanges object with peak center

 
# Generate peak center GRanges for the 10K top peaks
centers.BRG1 <- GRanges(seqnames(top.10000),
                        IRanges(start=top.10000$center.peak,
                                end=top.10000$center.peak))
  • Extend the ranges each side of 2000 bp using the function resize. Fill the parameters width and fix.

Show code: resize the peak regions

 
# Extend each side of 2000 bp
#extended.2K.BRG1 <- resize(centers.BRG1, width = width(centers.BRG1)+4000, fix = "center")
# Lucie : rencontre des soucis avec getTagMatrix : Error in getTagMatrix(peaks$BRG1, windows = extended.2K.BRG1) :
#windows should be made from getPromoters()/getBioRegion()/makeBioRegionFromGranges()
extended.2K.BRG1 <- makeBioRegionFromGranges(centers.BRG1,by="peaks", type= "start_site", upstream = 2000, downstream = 2000)
  • You now have the regions you want to map the peaks to. Create the matrix using the getTagMatrix function and the parameter windows. Display it with tagHeatmap and its parameters xlim and color which correspond to the presence of peaks in the region.

Show code: create the matrix and display the heatmap

 
## compute the density of peaks within the promoter regions
tagMatrix <- getTagMatrix(peaks$BRG1, windows=extended.2K.BRG1)
## >> preparing start_site regions by peaks... 2023-06-22 12:30:03
## >> preparing tag matrix...  2023-06-22 12:30:03
## plot the density
#tagHeatmap(tagMatrix, xlim=c(-2000, 2000), color="red")
tagHeatmap(tagMatrix)

The regions are ordered relative to their peak enrichment.

We can display a summary of the binding profiles by looking at the corresponding average profiles. This kind of profiles is much less greedy, we can thus extend a bit more (e.g. +/- 5000) from the peak centers redoing the previous steps. Definition of the regions have to be redone. Try to create the GRanges and the tagMatrix.

Show code: Extend 5000bp from TSS and create the matrix

 
# Extend from the peak center
#extended.5K.BRG1 <- resize(centers.BRG1, width = width(centers.BRG1)+10000, fix = "center")
#Lucie modif
extended.5K.BRG1 <- makeBioRegionFromGranges(centers.BRG1,by="peaks", type= "start_site", upstream = 5000, downstream = 5000)

## compute the density of peaks within the promoter regions
tagMatrix <- getTagMatrix(peaks$BRG1, windows=extended.5K.BRG1)
## >> preparing start_site regions by peaks... 2023-06-22 12:32:30
## >> preparing tag matrix...  2023-06-22 12:32:30


Use the plotAvgProf function defining the xlim and setting the labels of the x and y axis.

Show code: Plot the average profile of BRG1 binding

 
# Plot the profile
plotAvgProf(tagMatrix, xlim=c(-5000, 5000),
            xlab="Distance to peak center", ylab = "Peak Count Frequency")
## >> plotting figure...             2023-06-22 12:32:32

It looks like BRG1 is having several binding patterns but the binary nature of the signal (presence/absence of peaks) and row ordering do not allow us to appreciate them.

2.7.2 Read enrichment in BRG1 peaks

For computation and memory efficiency reasons, we are not going to analyse read coverage at the nucleotide resolution. The strategy is rather to compute coverage in equally sized windows (e.g. 20nt). We thus need to build a matrix composed of rows that are all BRG1 peaks and columns that contain read enrichment in all bins.

This allows to consider a bigger set of peaks and covered region. We will now analyze the whole set of BRG1 peaks over 10Kb (+/- 5000bp). We will ask for a hundred bins each side of the center resulting in 200 windows of 50 bp.

2.7.2.1 Prepare the signal matrices

We need to load bigwig files for all datasets that we want to visualize. Data are imported using a function from the rtracklayer package.


First, create the GRanges object containing centers of all the peaks and extend them each side of 5000 bp.

Show code: Create all peak center GRanges object and extend them

 
# # Generate peak center GRanges for all the peaks
centers.BRG1 <- GRanges(seqnames(peaks$BRG1),
                        IRanges(start=peaks$BRG1$center.peak,
                                end=peaks$BRG1$center.peak))
# Extend each side of 5000 bp
#extended.5K.BRG1 <- resize(centers.BRG1, width = width(centers.BRG1)+10000, fix = "center")
#Lucie modif
extended.5K.BRG1 <- makeBioRegionFromGranges(centers.BRG1,by="peaks", type= "start_site", upstream = 5000, downstream = 5000)

We then load the rtracklayer library and import the read coverage from a bigWig file.

# load the library
library(rtracklayer)
# load the bw file for BRG1
cvg.BRG1 <- import(paste0(params$chipseq,params$brg1.bw),format="BigWig",
                      which=extended.5K.BRG1,
                      as="RleList")
cvg.BRG1
## RleList of length 25
## $chr1
## numeric-Rle of length 248956422 with 1333289 runs
##   Lengths: 979000      3     48     15     32 ...   1288     73     36  22594
##   Values :   0.00   0.32   0.16   0.49   0.32 ...   0.00   0.17   0.33   0.00
## 
## $chr10
## numeric-Rle of length 133797422 with 510080 runs
##   Lengths: 368603    154     85    154    304 ...     90     58    154 272220
##   Values :   0.00   0.16   0.00   0.16   0.00 ...   0.65   0.00   0.33   0.00
## 
## $chr11
## numeric-Rle of length 135086622 with 542307 runs
##   Lengths: 202802     21    117    221     41 ...      9     70    154  74826
##   Values :   0.00   0.49   0.16   0.00   0.16 ...   0.16   0.00   0.16   0.00
## 
## $chr12
## numeric-Rle of length 133275309 with 564715 runs
##   Lengths: 194505     18    115    154    136 ...     22     68     19 189737
##   Values :   0.00   0.32   0.00   0.16   0.00 ...   0.16   0.65   0.49   0.00
## 
## $chr13
## numeric-Rle of length 114364328 with 338291 runs
##   Lengths: 19776001       19        5       12 ...       10       13    43427
##   Values :     0.00     1.29     1.13     0.97 ...     0.16     0.65     0.00
## 
## ...
## <20 more elements>

We can now create a matrix of read enrichment at the positions of interest with featureAlignedSignal from the ChIPpeakAnno package.


Load the library and find the required parameters. Be careful to the type of the required objects.

Show code: Create the read enrichment matrix

 
# load library
library(ChIPpeakAnno)
# featureAlignedSignal needs the coverage (cvg) stored in a list.
cvglist <- list(BRG1=cvg.BRG1)
sig <- featureAlignedSignal(cvglists = cvglist, feature.gr = centers.BRG1,n.tile=200,
                           upstream=5000, downstream=5000)
dim(sig$BRG1)
## [1] 30874   200

2.7.2.2 Create heatmaps

Let’s draw the heatmaps using the EnrichedHeatmap library. We need first to transform our enrichment matrix in an object readable for the EnrichedHeatmap function. We use the function as.normalizedMatrix for which many parameters need to be set. What do they control ?

## Load the library
library(EnrichedHeatmap)
## Create a list of normalizedMatrix that is the input format
## for EnrichedHeatmap
mat1 <- list()
mat1[["BRG1"]] <- as.normalizedMatrix(as.matrix(sig[["BRG1"]]),
    k_upstream = 100,
    k_downstream = 100,
    k_target = 0,
    extend = c(5000, 5000),
    signal_name = names(sig[["BRG1"]]),
    target_name = "Peak centers"
)
## Create the Heatmap with default parameters
EnrichedHeatmap(mat1$BRG1, name = "BRG1")

EnrichedHeatmap combines the average profile and the density heatmap. We can observe a greater precision of the signal around the peak centers. As with ChIPpeakAnno, by default, heatmaps are sorted by read enrichment. However, it would be worth grouping together regions that have similar read enrichment patterns. This can be done using a clustering method such as k-means. This type of clustering requires the number of expected clusters to be set. Moreover, to obtain reproducible clustering results, we need to set a seed.

## define a seed value to get the same results when re-running the analysis
set.seed(123)
## Create Heatmaps with k-means clustering on BRG1 data
## We keep the generated object in order to use the clustering
## information.
heatmap.kmeans <- EnrichedHeatmap(mat1$BRG1, name = "BRG1", row_km = 8,
    column_title = "BRG1", row_title_rot = 0)
## draw the heatmap
htlist <- draw(heatmap.kmeans)

Let’s enhance it!

  • We first retrieve the peak clusters from htlist object to use them as a pre-defined partition in our enhanced heatmap.
# Use the row_order function to retrieve peaks index
# belonging to each cluster
clusters <- row_order(htlist)
# rename the clusters
names(clusters) <- paste0("cluster",names(clusters))
# transform to a vector
# Check the class and length of the resulting object
class(clusters)
## [1] "list"
length(clusters)
## [1] 8
# Check what is actually in the list elements
head(clusters[[1]])
## [1]  1353 17624 22264  1564 19293 22270
# Each element of the list contain the indexes of the peaks in the
# original object
# Check cluster sizes
lapply(clusters,length)
## $cluster1
## [1] 1377
## 
## $cluster2
## [1] 1495
## 
## $cluster3
## [1] 1217
## 
## $cluster4
## [1] 1662
## 
## $cluster5
## [1] 1045
## 
## $cluster6
## [1] 5296
## 
## $cluster7
## [1] 5527
## 
## $cluster8
## [1] 13255
# create the partition by transforming the list in vector
partition <- unlist(clusters)
head(partition)
## cluster11 cluster12 cluster13 cluster14 cluster15 cluster16 
##      1353     17624     22264      1564     19293     22270
# names of the elements were extended with a number
# We thus trim them to retrieve the cluster name
names(partition) <- substring(first = 1,last = 8,text=names(partition))
# The numbers are the indexes of the rows, we need to
# sort the indexes to get the right order of cluster
# labels
partition <- names(partition)[order(partition)]

# keep this information with you BRG1 peaks
peaks$BRG1$cluster <- partition
head(peaks$BRG1)
## GRanges object with 6 ranges and 9 metadata columns:
##       seqnames          ranges strand |                     V4        V5
##          <Rle>       <IRanges>  <Rle> |            <character> <integer>
##   [1]     chr1   983476-984526      * | BRG1siCTRL_CHIP-seq_..       108
##   [2]     chr1 1000729-1001179      * | BRG1siCTRL_CHIP-seq_..        90
##   [3]     chr1 1020914-1021207      * | BRG1siCTRL_CHIP-seq_..       114
##   [4]     chr1 1069156-1070192      * | BRG1siCTRL_CHIP-seq_..        96
##   [5]     chr1 1079517-1080087      * | BRG1siCTRL_CHIP-seq_..       179
##   [6]     chr1 1304853-1306013      * | BRG1siCTRL_CHIP-seq_..       108
##                V6        V7        V8        V9       V10 center.peak
##       <character> <numeric> <numeric> <numeric> <integer>   <numeric>
##   [1]           .   5.97792   13.5966  10.83201       384      984001
##   [2]           .   6.65677   11.6289   9.01201       199     1000954
##   [3]           .   8.11634   14.2980  11.46427       158     1021060
##   [4]           .   6.90466   12.3485   9.65604       410     1069674
##   [5]           .   9.95583   21.2517  17.96153       213     1079802
##   [6]           .   5.97792   13.5966  10.83201       176     1305433
##           cluster
##       <character>
##   [1]    cluster8
##   [2]    cluster8
##   [3]    cluster8
##   [4]    cluster8
##   [5]    cluster8
##   [6]    cluster6
##   -------
##   seqinfo: 24 sequences from an unspecified genome; no seqlengths
  • Now, customize the enrichment colors and differentiate clusters with colors.
library(circlize)
# Define new colors for each heatmap
col_brg1 <- colorRamp2(c(0,10,15), c("white", "blue","black"))
# create a legend for the cluster labels
lgd <- Legend(at = c("cluster1", "cluster2", "cluster3", "cluster4","cluster5","cluster6","cluster7","cluster8"),
    title = "Clusters",
    type = "lines", legend_gp = gpar(col = 2:9))
# Add a first column containing the cluster assignment
ht_list <- Heatmap(partition, col = structure(2:9, names = paste0("cluster", 1:8)), name = "partition", show_row_names = FALSE, width = unit(3, "mm")) +
EnrichedHeatmap(mat1$BRG1, name = "BRG1", col=col_brg1, # specify the heat colors
  # color per cluster
  top_annotation = HeatmapAnnotation(lines = anno_enriched(gp = gpar(col = 2:9))),
  column_title = "BRG1")
draw(ht_list, split = partition, annotation_legend_list = list(lgd),
    ht_gap = unit(c(2, 8), "mm"))

2.7.2.3 Are BRG1 binding profiles associated with particular genomic regions ?

We will use here the clusters obtained with EnrichedHeatmap and look at the genomic distribution of peaks using TxDb.Hsapiens.UCSC.hg38.knownGene and plotAnnoBar.

# The following code uses each element of the list (peaks indexes)
# to select corresponding peaks in the original data and return them
BRG1.clusters <- lapply(clusters,function(x,peaks){
  # x represents one element of the list, one set of
  # indexes
  cl <- peaks[x]
  return(cl)
},peaks=peaks$BRG1)
# check names of the resulting list
names(BRG1.clusters)
## [1] "cluster1" "cluster2" "cluster3" "cluster4" "cluster5" "cluster6" "cluster7"
## [8] "cluster8"
# Transform the list as GRangesList to be able to use it with the annotatePeak
# function
BRG1.clusters <- as(BRG1.clusters,"GRangesList")
# apply annotatePeak function to each element of the BRG1.clusters GRangesList
peakAnnoList <- lapply(BRG1.clusters, annotatePeak, TxDb=txdb,
                       tssRegion=c(-1000, 100), annoDb="org.Hs.eg.db",
                       verbose=FALSE)
plotAnnoBar(peakAnnoList)

3 Data integration Cross-referencing data: let’s compare BRG1 to MITF and SOX10

3.1 Dataset description

3.1.1 Load MITF and SOX10 datasets

Using the readPeakFile function, add MITF (MITF_CHIP-seq_peaks.narrowPeak) and SOX10 (SOX10_CHIP-seq_peaks.narrowPeak) peaks to the peaks list. The path to these files is stored in the params list as the chipseq element.

Show code: Read MITF and SOX10 peak files

 
## Let's load MITF and SOX10 peak sets
peaks[["MITF"]] <- readPeakFile(paste0(params$chipseq, params$mitf), as="GRanges")
peaks[["SOX10"]] <- readPeakFile(paste0(params$chipseq, params$sox10), as="GRanges")

The list peaks now contains 3 elements.

length(peaks)
## [1] 3
names(peaks)
## [1] "BRG1"  "MITF"  "SOX10"

3.1.2 How many peaks were called?

We want to answer this question using a bar plot with ggplot2. Here we are basically plotting the same graphs as in section 2.2 with more data sets.

Try to create the command lines enabling to get a data.frame containing the number of peaks per chipped protein (use the sapply function to compute the length of each peak set). Then, plot the results as a bar plot filled with colors from the brewer palette “Set1” according to the TF name.

Show code: Plot peak set size per TF

 
# The `sapply` function makes now completely sense as we have a list with
# several elements to which we want to apply functions, here the length function.
peak.lengths <- data.frame(IP=names(peaks),
                           NbPeaks=sapply(peaks,length))
# check the object
peak.lengths
##          IP NbPeaks
## BRG1   BRG1   30874
## MITF   MITF    9702
## SOX10 SOX10    4538
ggplot(peak.lengths, aes(x=IP, y=NbPeaks, fill=IP)) +
         geom_col()+
         scale_fill_brewer(palette="Set1")+
        theme_classic()

3.1.3 How large are these peaks?

Compute statistics on all peak sizes as in section 2.3.

  • Compute the peak width within each peak set
  • Look at the structure of the return object (str())
  • Use the melt function from the reshape2 package to obtain a data.frame with one column with all the peak width and one column containing the name of the peak set they come from.

Show code: create a data.frame containing all peak widths

 
peak.width = lapply(peaks,width)
str(peak.width)
## List of 3
##  $ BRG1 : int [1:30874] 1051 451 294 1037 571 1161 360 285 897 905 ...
##  $ MITF : int [1:9702] 260 190 262 175 195 257 233 188 1251 317 ...
##  $ SOX10: int [1:4538] 252 272 331 517 253 362 246 306 254 400 ...
peak.width.table <- melt(peak.width)
head(peak.width.table)
##   value   L1
## 1  1051 BRG1
## 2   451 BRG1
## 3   294 BRG1
## 4  1037 BRG1
## 5   571 BRG1
## 6  1161 BRG1

In this table, there are as many rows as the total number of peaks in all peak sets. It contains all possible pairs IP <-> number of peaks possible.

# Number of peaks per chipped protein
sapply(peaks, length)
##  BRG1  MITF SOX10 
## 30874  9702  4538
# total number of peaks
sum(sapply(peaks, length))
## [1] 45114
# size of the table we've just generated
dim(peak.width.table)
## [1] 45114     2

We now want to represent the log transformed peak length distribution as boxplots filled with the corresponding colors. See bellow:

Show code: plot the distribution on peak length per experiment

 
ggplot(peak.width.table, aes(x=L1, y=value, fill=L1)) +
         geom_boxplot()+
         theme_classic()+
         scale_fill_brewer(palette="Set1")+
         labs(x = "", y = "log10(Peak sizes)", fill = "")+
         scale_y_log10()

3.2 Peak filtering

In order to discard poor quality peaks, a threshold is set on qValue. The following code aims at selecting peaks with a qValue greater than 4. The qValue corresponds to the 9th column of narrowPeak files. So, we are going to set a threshold on this.

## We will filter the peaks in each set using lapply. We first define
## a function to be applied to each set

filter_V9 <- function(x){
    res <- x[x$V9 >= 4,]
    return(res)
}

## Select high quality peaks in each element of the list peaks
peaks <- lapply(peaks, filter_V9)
## Compute the number of remaining peaks
sapply(peaks, length)
##  BRG1  MITF SOX10 
## 30874  9279  4214

3.2.1 Peak annotation

Load and add MITF and SOX10 annotations to the peakAnno list that already contains BRG1 annotations using annotatePeak as in 2.6.1.

Show code: annotate the peaks

 
peakAnno[["MITF"]] = annotatePeak(peaks$MITF, tssRegion=c(-1000, 100), TxDb=txdb, annoDb="org.Hs.eg.db")
## >> preparing features information...      2023-06-22 12:33:29 
## >> identifying nearest features...        2023-06-22 12:33:29 
## >> calculating distance from peak to TSS...   2023-06-22 12:33:30 
## >> assigning genomic annotation...        2023-06-22 12:33:30 
## >> adding gene annotation...          2023-06-22 12:33:32 
## >> assigning chromosome lengths           2023-06-22 12:33:32 
## >> done...                    2023-06-22 12:33:32
peakAnno[["SOX10"]] = annotatePeak(peaks$SOX10, tssRegion=c(-1000, 100), TxDb=txdb, annoDb="org.Hs.eg.db")
## >> preparing features information...      2023-06-22 12:33:32 
## >> identifying nearest features...        2023-06-22 12:33:32 
## >> calculating distance from peak to TSS...   2023-06-22 12:33:33 
## >> assigning genomic annotation...        2023-06-22 12:33:33 
## >> adding gene annotation...          2023-06-22 12:33:35 
## >> assigning chromosome lengths           2023-06-22 12:33:35 
## >> done...                    2023-06-22 12:33:35

And plot the distribution of genomic feature of the peaks as a barplot.

Show code: Plot genomic feature distribution per experiment

 
plotAnnoBar(peakAnno)

3.3 Are BRG1, MITF and SOX10 co-localizing ?

3.3.1 Compare BRG1, MITF and SOX10 peak positions (Venn Diagram)

Overlaps between peak datasets can be evaluated using a Venn diagram. Such approach is implemented in the ChIPpeakAnno package.

library(ChIPpeakAnno)
# We first compute the overlap between peak sets, keeping the information
# of all peaks overlapping in each set (see ?findOverlapsOfPeaks for help)
ovl <- findOverlapsOfPeaks(peaks, connectedPeaks="keepAll")

ChIPpeakAnno imposes, while plotting the Venn diagram, to compute the significance of the pairwise associations using a hypergeometric test. To this end, we need to estimate the number of all potential binding events which is used by the makeVennDiagram function through the totalTest number. It is used for the hypergeometric sampling that is used to determine if the overlap between two datasets is more than would be expected by chance. This is not a trivial question, the answer is driven by what you know about the binding properties of your factors (eg. sequence specific, mainly intergenic etc). You can find an interesting discussion here. In our case we can refer to the genomic distribution of the peaks that we have plotted previously. We can assume that our TFs have a gene body binding preference. Genes cover roughly 10% of the genome.

# Estimate the average size of the peaks ...
averagePeakWidth <- mean(width(unlist(GRangesList(ovl$peaklist))))
# ... to count how many potential sites could have been bound in coding regions.
tot <- ceiling(3.3e+9 * 0.1 / averagePeakWidth)

TIPS: We can define the colors attributed to each set using the function colours(). In any case you want to set a color you can use this function. Please, have a look to this page or more generally this page if you are interested in finely customizing colors of your plots.

makeVennDiagram(ovl, totalTest=tot, connectedPeaks="keepAll",
                fill=brewer.pal(3,"Set1"), # circle fill color
                col=brewer.pal(3,"Set1"), #circle border color
                cat.col=brewer.pal(3,"Set1"))

## INFO [2023-06-22 12:33:43] $fill
## INFO [2023-06-22 12:33:43] [1] "#E41A1C" "#377EB8" "#4DAF4A"
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $col
## INFO [2023-06-22 12:33:43] [1] "#E41A1C" "#377EB8" "#4DAF4A"
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $cat.col
## INFO [2023-06-22 12:33:43] [1] "#E41A1C" "#377EB8" "#4DAF4A"
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $cat.cex
## INFO [2023-06-22 12:33:43] [1] 1
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $cat.fontface
## INFO [2023-06-22 12:33:43] [1] "plain"
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $cat.fontfamily
## INFO [2023-06-22 12:33:43] [1] "serif"
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $x
## INFO [2023-06-22 12:33:43] $x$BRG1
## INFO [2023-06-22 12:33:43]     [1]  8098  8099  8100  8101  8102  8103  8104  8105  8106  8107  8108  8109
## INFO [2023-06-22 12:33:43]    [13]  8110  8111  8112  8113  8114  8115  8116  8117  8118  8119  8120  8121
## INFO [2023-06-22 12:33:43]    [25]  8122  8123  8124  8125  8126  8127  8128  8129  8130  8131  8132  8133
## INFO [2023-06-22 12:33:43]    [37]  8134  8135  8136  8137  8138  8139  8140  8141  8142  8143  8144  8145
## INFO [2023-06-22 12:33:43]    [49]  8146  8147  8148  8149  8150  8151  8152  8153  8154  8155  8156  8157
## INFO [2023-06-22 12:33:43]    [61]  8158  8159  8160  8161  8162  8163  8164  8165  8166  8167  8168  8169
## INFO [2023-06-22 12:33:43]    [73]  8170  8171  8172  8173  8174  8175  8176  8177  8178  8179  8180  8181
## INFO [2023-06-22 12:33:43]    [85]  8182  8183  8184  8185  8186  8187  8188  8189  8190  8191  8192  8193
## INFO [2023-06-22 12:33:43]    [97]  8194  8195  8196  8197  8198  8199  8200  8201  8202  8203  8204  8205
## INFO [2023-06-22 12:33:43]   [109]  8206  8207  8208  8209  8210  8211  8212  8213  8214  8215  8216  8217
## INFO [2023-06-22 12:33:43]   [121]  8218  8219  8220  8221  8222  8223  8224  8225  8226  8227  8228  8229
## INFO [2023-06-22 12:33:43]   [133]  8230  8231  8232  8233  8234  8235  8236  8237  8238  8239  8240  8241
## INFO [2023-06-22 12:33:43]   [145]  8242  8243  8244  8245  8246  8247  8248  8249  8250  8251  8252  8253
## INFO [2023-06-22 12:33:43]   [157]  8254  8255  8256  8257  8258  8259  8260  8261  8262  8263  8264  8265
## INFO [2023-06-22 12:33:43]   [169]  8266  8267  8268  8269  8270  8271  8272  8273  8274  8275  8276  8277
## INFO [2023-06-22 12:33:43]   [181]  8278  8279  8280  8281  8282  8283  8284  8285  8286  8287  8288  8289
## INFO [2023-06-22 12:33:43]   [193]  8290  8291  8292  8293  8294  8295  8296  8297  8298  8299  8300  8301
## INFO [2023-06-22 12:33:43]   [205]  8302  8303  8304  8305  8306  8307  8308  8309  8310  8311  8312  8313
## INFO [2023-06-22 12:33:43]   [217]  8314  8315  8316  8317  8318  8319  8320  8321  8322  8323  8324  8325
## INFO [2023-06-22 12:33:43]   [229]  8326  8327  8328  8329  8330  8331  8332  8333  8334  8335  8336  8337
## INFO [2023-06-22 12:33:43]   [241]  8338  8339  8340  8341  8342  8343  8344  8345  8346  8347  8348  8349
## INFO [2023-06-22 12:33:43]   [253]  8350  8351  8352  8353  8354  8355  8356  8357  8358  8359  8360  8361
## INFO [2023-06-22 12:33:43]   [265]  8362  8363  8364  8365  8366  8367  8368  8369  8370  8371  8372  8373
## INFO [2023-06-22 12:33:43]   [277]  8374  8375  8376  8377  8378  8379  8380  8381  8382  8383  8384  8385
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## INFO [2023-06-22 12:33:43]  [1957] 10054 10055 10056 10057 10058 10059 10060 10061 10062 10063 10064 10065
## INFO [2023-06-22 12:33:43]  [1969] 10066 10067 10068 10069 10070 10071 10072 10073 10074 10075 10076 10077
## INFO [2023-06-22 12:33:43]  [1981] 10078 10079 10080 10081 10082 10083 10084 10085 10086 10087 10088 10089
## INFO [2023-06-22 12:33:43]  [1993] 10090 10091 10092 10093 10094 10095 10096 10097 10098 10099 10100 10101
## INFO [2023-06-22 12:33:43]  [2005] 10102 10103 10104 10105 10106 10107 10108 10109 10110 10111 10112 10113
## INFO [2023-06-22 12:33:43]  [2017] 10114 10115 10116 10117 10118 10119 10120 10121 10122 10123 10124 10125
## INFO [2023-06-22 12:33:43]  [2029] 10126 10127 10128 10129 10130 10131 10132 10133 10134 10135 10136 10137
## INFO [2023-06-22 12:33:43]  [2041] 10138 10139 10140 10141 10142 10143 10144 10145 10146 10147 10148 10149
## INFO [2023-06-22 12:33:43]  [2053] 10150 10151 10152 10153 10154 10155 10156 10157 10158 10159 10160 10161
## INFO [2023-06-22 12:33:43]  [2065] 10162 10163 10164 10165 10166 10167 10168 10169 10170 10171 10172 10173
## INFO [2023-06-22 12:33:43]  [2077] 10174 10175 10176 10177 10178 10179 10180 10181 10182 10183 10184 10185
## INFO [2023-06-22 12:33:43]  [2089] 10186 10187 10188 10189 10190 10191 10192 10193 10194 10195 10196 10197
## INFO [2023-06-22 12:33:43]  [2101] 10198 10199 10200 10201 10202 10203 10204 10205 10206 10207 10208 10209
## INFO [2023-06-22 12:33:43]  [2113] 10210 10211 10212 10213 10214 10215 10216 10217 10218 10219 10220 10221
## INFO [2023-06-22 12:33:43]  [2125] 10222 10223 10224 10225 10226 10227 10228 10229 10230 10231 10232 10233
## INFO [2023-06-22 12:33:43]  [2137] 10234 10235 10236 10237 10238 10239 10240 10241 10242 10243 10244 10245
## INFO [2023-06-22 12:33:43]  [2149] 10246 10247 10248 10249 10250 10251 10252 10253 10254 10255 10256 10257
## INFO [2023-06-22 12:33:43]  [2161] 10258 10259 10260 10261 10262 10263 10264 10265 10266 10267 10268 10269
## INFO [2023-06-22 12:33:43]  [2173] 10270 10271 10272 10273 10274 10275 10276 10277 10278 10279 10280 10281
## INFO [2023-06-22 12:33:43]  [2185] 10282 10283 10284 10285 10286 10287 10288 10289 10290 10291 10292 10293
## INFO [2023-06-22 12:33:43]  [2197] 10294 10295 10296 10297 10298 10299 10300 10301 10302 10303 10304 10305
## INFO [2023-06-22 12:33:43]  [2209] 10306 10307 10308 10309 10310 10311 10312 10313 10314 10315 10316 10317
## INFO [2023-06-22 12:33:43]  [2221] 10318 10319 10320 10321 10322 10323 10324 10325 10326 10327 10328 10329
## INFO [2023-06-22 12:33:43]  [2233] 10330 10331 10332 10333 10334 10335 10336 10337 10338 10339 10340 10341
## INFO [2023-06-22 12:33:43]  [2245] 10342 10343 10344 10345 10346 10347 10348 10349 10350 10351 10352 10353
## INFO [2023-06-22 12:33:43]  [2257] 10354 10355 10356 10357 10358 10359 10360 10361 10362 10363 10364 10365
## INFO [2023-06-22 12:33:43]  [2269] 10366 10367 10368 10369 10370 10371 10372 10373 10374 10375 10376 10377
## INFO [2023-06-22 12:33:43]  [2281] 10378 10379 10380 10381 10382 10383 10384 10385 10386 10387 10388 10389
## INFO [2023-06-22 12:33:43]  [2293] 10390 10391 10392 10393 10394 10395 10396 10397 10398 10399 10400 10401
## INFO [2023-06-22 12:33:43]  [2305] 10402 10403 10404 10405 10406 10407 10408 10409 10410 10411 10412 10413
## INFO [2023-06-22 12:33:43]  [2317] 10414 10415 10416 10417 10418 10419 10420 10421 10422 10423 10424 10425
## INFO [2023-06-22 12:33:43]  [2329] 10426 10427 10428 10429 10430 10431 10432 10433 10434 10435 10436 10437
## INFO [2023-06-22 12:33:43]  [2341] 10438 10439 10440 10441 10442 10443 10444 10445 10446 10447 10448 10449
## INFO [2023-06-22 12:33:43]  [2353] 10450 10451 10452 10453 10454 10455 10456 10457 10458 10459 10460 10461
## INFO [2023-06-22 12:33:43]  [2365] 10462 10463 10464 10465 10466 10467 10468 10469 10470 10471 10472 10473
## INFO [2023-06-22 12:33:43]  [2377] 10474 10475 10476 10477 10478 10479 10480 10481 10482 10483 10484 10485
## INFO [2023-06-22 12:33:43]  [2389] 10486 10487 10488 10489 10490 10491 10492 10493 10494 10495 10496 10497
## INFO [2023-06-22 12:33:43]  [2401] 10498 10499 10500 10501 10502 10503 10504 10505 10506 10507 10508 10509
## INFO [2023-06-22 12:33:43]  [2413] 10510 10511 10512 10513 10514 10515 10516 10517 10518 10519 10520 10521
## INFO [2023-06-22 12:33:43]  [2425] 10522 10523 10524 10525 10526 10527 10528 10529 10530 10531 10532 10533
## INFO [2023-06-22 12:33:43]  [2437] 10534 10535 10536 10537 10538 10539 10540 10541 10542 10543 10544 10545
## INFO [2023-06-22 12:33:43]  [2449] 10546 10547 10548 10549 10550 10551 10552 10553 10554 10555 10556 10557
## INFO [2023-06-22 12:33:43]  [2461] 10558 10559 10560 10561 10562 10563 10564 10565 10566 10567 10568 10569
## INFO [2023-06-22 12:33:43]  [2473] 10570 10571 10572 10573 10574 10575 10576 10577 10578 10579 10580 10581
## INFO [2023-06-22 12:33:43]  [2485] 10582 10583 10584 10585 10586 10587 10588 10589 10590 10591 10592 10593
## INFO [2023-06-22 12:33:43]  [2497] 10594 10595 10596 10597 10598 10599 10600 10601 10602 10603 10604 10605
## INFO [2023-06-22 12:33:43]  [2509] 10606 10607 10608 10609 10610 10611 10612 10613 10614 10615 10616 10617
## INFO [2023-06-22 12:33:43]  [2521] 10618 10619 10620 10621 10622 10623 10624 10625 10626 10627 10628 10629
## INFO [2023-06-22 12:33:43]  [2533] 10630 10631 10632 10633 10634 10635 10636 10637 10638 10639 10640 10641
## INFO [2023-06-22 12:33:43]  [2545] 10642 10643 10644 10645 10646 10647 10648 10649 10650 10651 10652 10653
## INFO [2023-06-22 12:33:43]  [2557] 10654 10655 10656 10657 10658 10659 10660 10661 10662 10663 10664 10665
## INFO [2023-06-22 12:33:43]  [2569] 10666 10667 10668 10669 10670 10671 10672 10673 10674 10675 10676 10677
## INFO [2023-06-22 12:33:43]  [2581] 10678 10679 10680 10681 10682 10683 10684 10685 10686 10687 10688 10689
## INFO [2023-06-22 12:33:43]  [2593] 10690 10691 10692 10693 10694 10695 10696 10697 10698 10699 10700 10701
## INFO [2023-06-22 12:33:43]  [2605] 10702 10703 10704 10705 10706 10707 10708 10709 10710 10711 10712 10713
## INFO [2023-06-22 12:33:43]  [2617] 10714 10715 10716 10717 10718 10719 10720 10721 10722 10723 10724 10725
## INFO [2023-06-22 12:33:43]  [2629] 10726 10727 10728 10729 10730 10731 10732 10733 10734 10735 10736 10737
## INFO [2023-06-22 12:33:43]  [2641] 10738 10739 10740 10741 10742 10743 10744 10745 10746 10747 10748 10749
## INFO [2023-06-22 12:33:43]  [2653] 10750 10751 10752 10753 10754 10755 10756 10757 10758 10759 10760 10761
## INFO [2023-06-22 12:33:43]  [2665] 10762 10763 10764 10765 10766 10767 10768 10769 10770 10771 10772 10773
## INFO [2023-06-22 12:33:43]  [2677] 10774 10775 10776 10777 10778 10779 10780 10781 10782 10783 10784 10785
## INFO [2023-06-22 12:33:43]  [2689] 10786 10787 10788 10789 10790 10791 10792 10793 10794 10795 10796 10797
## INFO [2023-06-22 12:33:43]  [2701] 10798 10799 10800 10801 10802 10803 10804 10805 10806 10807 10808 10809
## INFO [2023-06-22 12:33:43]  [2713] 10810 10811 10812 10813 10814 10815 10816 10817 10818 10819 10820 10821
## INFO [2023-06-22 12:33:43]  [2725] 10822 10823 10824 10825 10826 10827 10828 10829 10830 10831 10832 10833
## INFO [2023-06-22 12:33:43]  [2737] 10834 10835 10836 10837 10838 10839 10840 10841 10842 10843 10844 10845
## INFO [2023-06-22 12:33:43]  [2749] 10846 10847 10848 10849 10850 10851 10852 10853 10854 10855 10856 10857
## INFO [2023-06-22 12:33:43]  [2761] 10858 10859 10860 10861 10862 10863 10864 10865 10866 10867 10868 10869
## INFO [2023-06-22 12:33:43]  [2773] 10870 10871 10872 10873 10874 10875 10876 10877 10878 10879 10880 10881
## INFO [2023-06-22 12:33:43]  [2785] 10882 10883 10884 10885 10886 10887 10888 10889 10890 10891 10892 10893
## INFO [2023-06-22 12:33:43]  [2797] 10894 10895 10896 10897 10898 10899 10900 10901 10902 10903 10904 10905
## INFO [2023-06-22 12:33:43]  [2809] 10906 10907 10908 10909 10910 10911 10912 10913 10914 10915 10916 10917
## INFO [2023-06-22 12:33:43]  [2821] 10918 10919 10920 10921 10922 10923 10924 10925 10926 10927 10928 10929
## INFO [2023-06-22 12:33:43]  [2833] 10930 10931 10932 10933 10934 10935 10936 10937 10938 10939 10940 10941
## INFO [2023-06-22 12:33:43]  [2845] 10942 10943 10944 10945 10946 10947 10948 10949 10950 10951 10952 10953
## INFO [2023-06-22 12:33:43]  [2857] 10954 10955 10956 10957 10958 10959 10960 10961 10962 10963 10964 10965
## INFO [2023-06-22 12:33:43]  [2869] 10966 10967 10968 10969 10970 10971 10972 10973 10974 10975 10976 10977
## INFO [2023-06-22 12:33:43]  [2881] 10978 10979 10980 10981 10982 10983 10984 10985 10986 10987 10988 10989
## INFO [2023-06-22 12:33:43]  [2893] 10990 10991 10992 10993 10994 10995 10996 10997 10998 10999 11000 11001
## INFO [2023-06-22 12:33:43]  [2905] 11002 11003 11004 11005 11006 11007 11008 11009 11010 11011 11012 11013
## INFO [2023-06-22 12:33:43]  [2917] 11014 11015 11016 11017 11018 11019 11020 11021 11022 11023 11024 11025
## INFO [2023-06-22 12:33:43]  [2929] 11026 11027 11028 11029 11030 11031 11032 11033 11034 11035 11036 11037
## INFO [2023-06-22 12:33:43]  [2941] 11038 11039 11040 11041 11042 11043 11044 11045 11046 11047 11048 11049
## INFO [2023-06-22 12:33:43]  [2953] 11050 11051 11052 11053 11054 11055 11056 11057 11058 11059 11060 11061
## INFO [2023-06-22 12:33:43]  [2965] 11062 11063 11064 11065 11066 11067 11068 11069 11070 11071 11072 11073
## INFO [2023-06-22 12:33:43]  [2977] 11074 11075 11076 11077 11078 11079 11080 11081 11082 11083 11084 11085
## INFO [2023-06-22 12:33:43]  [2989] 11086 11087 11088 11089 11090 11091 11092 11093 11094 11095 11096 11097
## INFO [2023-06-22 12:33:43]  [3001] 11098 11099 11100 11101 11102 11103 11104 11105 11106 11107 11108 11109
## INFO [2023-06-22 12:33:43]  [3013] 11110 11111 11112 11113 11114 11115 11116 11117 11118 11119 11120 11121
## INFO [2023-06-22 12:33:43]  [3025] 11122 11123 11124 11125 11126 11127 11128 11129 11130 11131 11132 11133
## INFO [2023-06-22 12:33:43]  [3037] 11134 11135 11136 11137 11138 11139 11140 11141 11142 11143 11144 11145
## INFO [2023-06-22 12:33:43]  [3049] 11146 11147 11148 11149 11150 11151 11152 11153 11154 11155 11156 11157
## INFO [2023-06-22 12:33:43]  [3061] 11158 11159 11160 11161 11162 11163 11164 11165 11166 11167 11168 11169
## INFO [2023-06-22 12:33:43]  [3073] 11170 11171 11172 11173 11174 11175 11176 11177 11178 11179 11180 11181
## INFO [2023-06-22 12:33:43]  [3085] 11182 11183 11184 11185 11186 11187 11188 11189 11190 11191 11192 11193
## INFO [2023-06-22 12:33:43]  [3097] 11194 11195 11196 11197 11198 11199 11200 11201 11202 11203 11204 11205
## INFO [2023-06-22 12:33:43]  [3109] 11206 11207 11208 11209 11210 11211 11212 11213 11214 11215 11216 11217
## INFO [2023-06-22 12:33:43]  [3121] 11218 11219 11220 11221 11222 11223 11224 11225 11226 11227 11228 11229
## INFO [2023-06-22 12:33:43]  [3133] 11230 11231 11232 11233 11234 11235 11236 11237 11238 11239 11240 11241
## INFO [2023-06-22 12:33:43]  [3145] 11242 11243 11244 11245 11246 11247 11248 11249 11250 11251 11252 11253
## INFO [2023-06-22 12:33:43]  [3157] 11254 11255 11256 11257 11258 11259 11260 11261 11262 11263 11264 11265
## INFO [2023-06-22 12:33:43]  [3169] 11266 11267 11268 11269 11270 11271 11272 11273 11274 11275 11276 11277
## INFO [2023-06-22 12:33:43]  [3181] 11278 11279 11280 11281 11282 11283 11284 11285 11286 11287 11288 11289
## INFO [2023-06-22 12:33:43]  [3193] 11290 11291 11292 11293 11294 11295 11296 11297 11298 11299 11300 11301
## INFO [2023-06-22 12:33:43]  [3205] 11302 11303 11304 11305 11306 11307 11308 11309 11310 11311 11312 11313
## INFO [2023-06-22 12:33:43]  [3217] 11314 11315 11316 11317 11318 11319 11320 11321 11322 11323 11324 11325
## INFO [2023-06-22 12:33:43]  [3229] 11326 11327 11328 11329 11330 11331 11332 11333 11334 11335 11336 11337
## INFO [2023-06-22 12:33:43]  [3241] 11338 11339 11340 11341 11342 11343 11344 11345 11346 11347 11348 11349
## INFO [2023-06-22 12:33:43]  [3253] 11350 11351 11352 11353 11354 11355 11356 11357 11358 11359 11360 11361
## INFO [2023-06-22 12:33:43]  [3265] 11362 11363 11364 11365 11366 11367 11368 11369 11370 11371 11372 11373
## INFO [2023-06-22 12:33:43]  [3277] 11374 11375 11376 11377 11378 11379 11380 11381 11382 11383 11384 11385
## INFO [2023-06-22 12:33:43]  [3289] 11386 11387 11388 11389 11390 11391 11392 11393 11394 11395 11396 11397
## INFO [2023-06-22 12:33:43]  [3301] 11398 11399 11400 11401 11402 11403 11404 11405 11406 11407 11408 11409
## INFO [2023-06-22 12:33:43]  [3313] 11410 11411 11412 11413 11414 11415 11416 11417 11418 11419 11420 11421
## INFO [2023-06-22 12:33:43]  [3325] 11422 11423 11424 11425 11426 11427 11428 11429 11430 11431 11432 11433
## INFO [2023-06-22 12:33:43]  [3337] 11434 11435 11436 11437 11438 11439 11440 11441 11442 11443 11444 11445
## INFO [2023-06-22 12:33:43]  [3349] 11446 11447 11448 11449 11450 11451 11452 11453 11454 11455 11456 11457
## INFO [2023-06-22 12:33:43]  [3361] 11458 11459 11460 11461 11462 11463 11464 11465 11466 11467 11468 11469
## INFO [2023-06-22 12:33:43]  [3373] 11470 11471 11472 11473 11474 11475 11476 11477 11478 11479 11480 11481
## INFO [2023-06-22 12:33:43]  [3385] 11482 11483 11484 11485 11486 11487 11488 11489 11490 11491 11492 11493
## INFO [2023-06-22 12:33:43]  [3397] 11494 11495 11496 11497 11498 11499 11500 11501 11502 11503 11504 11505
## INFO [2023-06-22 12:33:43]  [3409] 11506 11507 11508 11509 11510 11511 11512 11513 11514 11515 11516 11517
## INFO [2023-06-22 12:33:43]  [3421] 11518 11519 11520 11521 11522 11523 11524 11525 11526 11527 11528 11529
## INFO [2023-06-22 12:33:43]  [3433] 11530 11531 11532 11533 11534 11535 11536 11537 11538 11539 11540 11541
## INFO [2023-06-22 12:33:43]  [3445] 11542 11543 11544 11545 11546 11547 11548 11549 11550 11551 11552 11553
## INFO [2023-06-22 12:33:43]  [3457] 11554 11555 11556 11557 11558 11559 11560 11561 11562 11563 11564 11565
## INFO [2023-06-22 12:33:43]  [3469] 11566 11567 11568 11569 11570 11571 11572 11573 11574 11575 11576 11577
## INFO [2023-06-22 12:33:43]  [3481] 11578 11579 11580 11581 11582 11583 11584 11585 11586 11587 11588 11589
## INFO [2023-06-22 12:33:43]  [3493] 11590 11591 11592 11593 11594 11595 11596 11597 11598 11599 11600 11601
## INFO [2023-06-22 12:33:43]  [3505] 11602 11603 11604 11605 11606 11607 11608 11609 11610 11611 11612 11613
## INFO [2023-06-22 12:33:43]  [3517] 11614 11615 11616 11617 11618 11619 11620 11621 11622 11623 11624 11625
## INFO [2023-06-22 12:33:43]  [3529] 11626 11627 11628 11629 11630 11631 11632 11633 11634 11635 11636 11637
## INFO [2023-06-22 12:33:43]  [3541] 11638 11639 11640 11641 11642 11643 11644 11645 11646 11647 11648 11649
## INFO [2023-06-22 12:33:43]  [3553] 11650 11651 11652 11653 11654 11655 11656 11657 11658 11659 11660 11661
## INFO [2023-06-22 12:33:43]  [3565] 11662 11663 11664 11665 11666 11667 11668 11669 11670 11671 11672 11673
## INFO [2023-06-22 12:33:43]  [3577] 11674 11675 11676 11677 11678 11679 11680 11681 11682 11683 11684 11685
## INFO [2023-06-22 12:33:43]  [3589] 11686 11687 11688 11689 11690 11691 11692 11693 11694 11695 11696 11697
## INFO [2023-06-22 12:33:43]  [3601] 11698 11699 11700 11701 11702 11703 11704 11705 11706 11707 11708 11709
## INFO [2023-06-22 12:33:43]  [3613] 11710 11711 11712 11713 11714 11715 11716 11717 11718 11719 11720 11721
## INFO [2023-06-22 12:33:43]  [3625] 11722 11723 11724 11725 11726 11727 11728 11729 11730 11731 11732 11733
## INFO [2023-06-22 12:33:43]  [3637] 11734 11735 11736 11737 11738 11739 11740 11741 11742 11743 11744 11745
## INFO [2023-06-22 12:33:43]  [3649] 11746 11747 11748 11749 11750 11751 11752 11753 11754 11755 11756 11757
## INFO [2023-06-22 12:33:43]  [3661] 11758 11759 11760 11761 11762 11763 11764 11765 11766 11767 11768 11769
## INFO [2023-06-22 12:33:43]  [3673] 11770 11771 11772 11773 11774 11775 11776 11777 11778 11779 11780 11781
## INFO [2023-06-22 12:33:43]  [3685] 11782 11783 11784 11785 11786 11787 11788 11789 11790 11791 11792 11793
## INFO [2023-06-22 12:33:43]  [3697] 11794 11795 11796 11797 11798 11799 11800 11801 11802 11803 11804 11805
## INFO [2023-06-22 12:33:43]  [3709] 11806 11807 11808 11809 11810 11811 11812 11813 11814 11815 11816 11817
## INFO [2023-06-22 12:33:43]  [3721] 11818 11819 11820 11821 11822 11823 11824 11825 11826 11827 11828 11829
## INFO [2023-06-22 12:33:43]  [3733] 11830 11831 11832 11833 11834 11835 11836 11837 11838 11839 11840 11841
## INFO [2023-06-22 12:33:43]  [3745] 11842 11843 11844 11845 11846 11847 11848 11849 11850 11851 11852 11853
## INFO [2023-06-22 12:33:43]  [3757] 11854 11855 11856 11857 11858 11859 11860 11861 11862 11863 11864 11865
## INFO [2023-06-22 12:33:43]  [3769] 11866 11867 11868 11869 11870 11871 11872 11873 11874 11875 11876 11877
## INFO [2023-06-22 12:33:43]  [3781] 11878 11879 11880 11881 11882 11883 11884 11885 11886 11887 11888 11889
## INFO [2023-06-22 12:33:43]  [3793] 11890 11891 11892 11893 11894 11895 11896 11897 11898 11899 11900 11901
## INFO [2023-06-22 12:33:43]  [3805] 11902 11903 11904 11905 11906 11907 11908 11909 11910 11911 11912 11913
## INFO [2023-06-22 12:33:43]  [3817] 11914 11915 11916 11917 11918 11919 11920 11921 11922 11923 11924 11925
## INFO [2023-06-22 12:33:43]  [3829] 11926 11927 11928 11929 11930 11931 11932 11933 11934 11935 11936 11937
## INFO [2023-06-22 12:33:43]  [3841] 11938 11939 11940 11941 11942 11943 11944 11945 11946 11947 11948 11949
## INFO [2023-06-22 12:33:43]  [3853] 11950 11951 11952 11953 11954 11955 11956 11957 11958 11959 11960 11961
## INFO [2023-06-22 12:33:43]  [3865] 11962 11963 11964 11965 11966 11967 11968 11969 11970 11971 11972 11973
## INFO [2023-06-22 12:33:43]  [3877] 11974 11975 11976 11977 11978 11979 11980 11981 11982 11983 11984 11985
## INFO [2023-06-22 12:33:43]  [3889] 11986 11987 11988 11989 11990 11991 11992 11993 11994 11995 11996 11997
## INFO [2023-06-22 12:33:43]  [3901] 11998 11999 12000 12001 12002 12003 12004 12005 12006 12007 12008 12009
## INFO [2023-06-22 12:33:43]  [3913] 12010 12011 12012 12013 12014 12015 12016 12017 12018 12019 12020 12021
## INFO [2023-06-22 12:33:43]  [3925] 12022 12023 12024 12025 12026 12027 12028 12029 12030 12031 12032 12033
## INFO [2023-06-22 12:33:43]  [3937] 12034 12035 12036 12037 12038 12039 12040 12041 12042 12043 12044 12045
## INFO [2023-06-22 12:33:43]  [3949] 12046 12047 12048 12049 12050 12051 12052 12053 12054 12055 12056 12057
## INFO [2023-06-22 12:33:43]  [3961] 12058 12059 12060 12061 12062 12063 12064 12065 12066 12067 12068 12069
## INFO [2023-06-22 12:33:43]  [3973] 12070 12071 12072 12073 12074 12075 12076 12077 12078 12079 12080 12081
## INFO [2023-06-22 12:33:43]  [3985] 12082 12083 12084 12085 12086 12087 12088 12089 12090 12091 12092 12093
## INFO [2023-06-22 12:33:43]  [3997] 12094 12095 12096 12097 12098 12099 12100 12101 12102 12103 12104 12105
## INFO [2023-06-22 12:33:43]  [4009] 12106 12107 12108 12109 12110 12111 12112 12113 12114 12115 12116 12117
## INFO [2023-06-22 12:33:43]  [4021] 12118 12119 12120 12121 12122 12123 12124 12125 12126 12127 12128 12129
## INFO [2023-06-22 12:33:43]  [4033] 12130 12131 12132 12133 12134 12135 12136 12137 12138 12139 12140 12141
## INFO [2023-06-22 12:33:43]  [4045] 12142 12143 12144 12145 12146 12147 12148 12149 12150 12151 12152 12153
## INFO [2023-06-22 12:33:43]  [4057] 12154 12155 12156 12157 12158 12159 12160 12161 12162 12163 12164 12165
## INFO [2023-06-22 12:33:43]  [4069] 12166 12167 12168 12169 12170 12171 12172 12173 12174 12175 12176 12177
## INFO [2023-06-22 12:33:43]  [4081] 12178 12179 12180 12181 12182 12183 12184 12185 12186 12187 12188 12189
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## INFO [2023-06-22 12:33:43]  [4201] 12298 12299 12300 12301 12302 12303 12304 12305 12306 12307 12308 12309
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## INFO [2023-06-22 12:33:43]  [4369] 12466 12467 12468 12469 12470 12471 12472 12473 12474 12475 12476 12477
## INFO [2023-06-22 12:33:43]  [4381] 12478 12479 12480 12481 12482 12483 12484 12485 12486 12487 12488 12489
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## INFO [2023-06-22 12:33:43]  [4621] 12718 12719 12720 12721 12722 12723 12724 12725 12726 12727 12728 12729
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## INFO [2023-06-22 12:33:43]  [4669] 12766 12767 12768 12769 12770 12771 12772 12773 12774 12775 12776 12777
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## INFO [2023-06-22 12:33:43]  [4693] 12790 12791 12792 12793 12794 12795 12796 12797 12798 12799 12800 12801
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## INFO [2023-06-22 12:33:43]  [4741] 12838 12839 12840 12841 12842 12843 12844 12845 12846 12847 12848 12849
## INFO [2023-06-22 12:33:43]  [4753] 12850 12851 12852 12853 12854 12855 12856 12857 12858 12859 12860 12861
## INFO [2023-06-22 12:33:43]  [4765] 12862 12863 12864 12865 12866 12867 12868 12869 12870 12871 12872 12873
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## INFO [2023-06-22 12:33:43]  [4801] 12898 12899 12900 12901 12902 12903 12904 12905 12906 12907 12908 12909
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## INFO [2023-06-22 12:33:43]  [4969] 13066 13067 13068 13069 13070 13071 13072 13073 13074 13075 13076 13077
## INFO [2023-06-22 12:33:43]  [4981] 13078 13079 13080 13081 13082 13083 13084 13085 13086 13087 13088 13089
## INFO [2023-06-22 12:33:43]  [4993] 13090 13091 13092 13093 13094 13095 13096 13097 13098 13099 13100 13101
## INFO [2023-06-22 12:33:43]  [5005] 13102 13103 13104 13105 13106 13107 13108 13109 13110 13111 13112 13113
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## INFO [2023-06-22 12:33:43]  [5029] 13126 13127 13128 13129 13130 13131 13132 13133 13134 13135 13136 13137
## INFO [2023-06-22 12:33:43]  [5041] 13138 13139 13140 13141 13142 13143 13144 13145 13146 13147 13148 13149
## INFO [2023-06-22 12:33:43]  [5053] 13150 13151 13152 13153 13154 13155 13156 13157 13158 13159 13160 13161
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## INFO [2023-06-22 12:33:43]  [5089] 13186 13187 13188 13189 13190 13191 13192 13193 13194 13195 13196 13197
## INFO [2023-06-22 12:33:43]  [5101] 13198 13199 13200 13201 13202 13203 13204 13205 13206 13207 13208 13209
## INFO [2023-06-22 12:33:43]  [5113] 13210 13211 13212 13213 13214 13215 13216 13217 13218 13219 13220 13221
## INFO [2023-06-22 12:33:43]  [5125] 13222 13223 13224 13225 13226 13227 13228 13229 13230 13231 13232 13233
## INFO [2023-06-22 12:33:43]  [5137] 13234 13235 13236 13237 13238 13239 13240 13241 13242 13243 13244 13245
## INFO [2023-06-22 12:33:43]  [5149] 13246 13247 13248 13249 13250 13251 13252 13253 13254 13255 13256 13257
## INFO [2023-06-22 12:33:43]  [5161] 13258 13259 13260 13261 13262 13263 13264 13265 13266 13267 13268 13269
## INFO [2023-06-22 12:33:43]  [5173] 13270 13271 13272 13273 13274 13275 13276 13277 13278 13279 13280 13281
## INFO [2023-06-22 12:33:43]  [5185] 13282 13283 13284 13285 13286 13287 13288 13289 13290 13291 13292 13293
## INFO [2023-06-22 12:33:43]  [5197] 13294 13295 13296 13297 13298 13299 13300 13301 13302 13303 13304 13305
## INFO [2023-06-22 12:33:43]  [5209] 13306 13307 13308 13309 13310 13311 13312 13313 13314 13315 13316 13317
## INFO [2023-06-22 12:33:43]  [5221] 13318 13319 13320 13321 13322 13323 13324 13325 13326 13327 13328 13329
## INFO [2023-06-22 12:33:43]  [5233] 13330 13331 13332 13333 13334 13335 13336 13337 13338 13339 13340 13341
## INFO [2023-06-22 12:33:43]  [5245] 13342 13343 13344 13345 13346 13347 13348 13349 13350 13351 13352 13353
## INFO [2023-06-22 12:33:43]  [5257] 13354 13355 13356 13357 13358 13359 13360 13361 13362 13363 13364 13365
## INFO [2023-06-22 12:33:43]  [5269] 13366 13367 13368 13369 13370 13371 13372 13373 13374 13375 13376 13377
## INFO [2023-06-22 12:33:43]  [5281] 13378 13379 13380 13381 13382 13383 13384 13385 13386 13387 13388 13389
## INFO [2023-06-22 12:33:43]  [5293] 13390 13391 13392 13393 13394 13395 13396 13397 13398 13399 13400 13401
## INFO [2023-06-22 12:33:43]  [5305] 13402 13403 13404 13405 13406 13407 13408 13409 13410 13411 13412 13413
## INFO [2023-06-22 12:33:43]  [5317] 13414 13415 13416 13417 13418 13419 13420 13421 13422 13423 13424 13425
## INFO [2023-06-22 12:33:43]  [5329] 13426 13427 13428 13429 13430 13431 13432 13433 13434 13435 13436 13437
## INFO [2023-06-22 12:33:43]  [5341] 13438 13439 13440 13441 13442 13443 13444 13445 13446 13447 13448 13449
## INFO [2023-06-22 12:33:43]  [5353] 13450 13451 13452 13453 13454 13455 13456 13457 13458 13459 13460 13461
## INFO [2023-06-22 12:33:43]  [5365] 13462 13463 13464 13465 13466 13467 13468 13469 13470 13471 13472 13473
## INFO [2023-06-22 12:33:43]  [5377] 13474 13475 13476 13477 13478 13479 13480 13481 13482 13483 13484 13485
## INFO [2023-06-22 12:33:43]  [5389] 13486 13487 13488 13489 13490 13491 13492 13493 13494 13495 13496 13497
## INFO [2023-06-22 12:33:43]  [5401] 13498 13499 13500 13501 13502 13503 13504 13505 13506 13507 13508 13509
## INFO [2023-06-22 12:33:43]  [5413] 13510 13511 13512 13513 13514 13515 13516 13517 13518 13519 13520 13521
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## INFO [2023-06-22 12:33:43]  [5437] 13534 13535 13536 13537 13538 13539 13540 13541 13542 13543 13544 13545
## INFO [2023-06-22 12:33:43]  [5449] 13546 13547 13548 13549 13550 13551 13552 13553 13554 13555 13556 13557
## INFO [2023-06-22 12:33:43]  [5461] 13558 13559 13560 13561 13562 13563 13564 13565 13566 13567 13568 13569
## INFO [2023-06-22 12:33:43]  [5473] 13570 13571 13572 13573 13574 13575 13576 13577 13578 13579 13580 13581
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## INFO [2023-06-22 12:33:43]  [5497] 13594 13595 13596 13597 13598 13599 13600 13601 13602 13603 13604 13605
## INFO [2023-06-22 12:33:43]  [5509] 13606 13607 13608 13609 13610 13611 13612 13613 13614 13615 13616 13617
## INFO [2023-06-22 12:33:43]  [5521] 13618 13619 13620 13621 13622 13623 13624 13625 13626 13627 13628 13629
## INFO [2023-06-22 12:33:43]  [5533] 13630 13631 13632 13633 13634 13635 13636 13637 13638 13639 13640 13641
## INFO [2023-06-22 12:33:43]  [5545] 13642 13643 13644 13645 13646 13647 13648 13649 13650 13651 13652 13653
## INFO [2023-06-22 12:33:43]  [5557] 13654 13655 13656 13657 13658 13659 13660 13661 13662 13663 13664 13665
## INFO [2023-06-22 12:33:43]  [5569] 13666 13667 13668 13669 13670 13671 13672 13673 13674 13675 13676 13677
## INFO [2023-06-22 12:33:43]  [5581] 13678 13679 13680 13681 13682 13683 13684 13685 13686 13687 13688 13689
## INFO [2023-06-22 12:33:43]  [5593] 13690 13691 13692 13693 13694 13695 13696 13697 13698 13699 13700 13701
## INFO [2023-06-22 12:33:43]  [5605] 13702 13703 13704 13705 13706 13707 13708 13709 13710 13711 13712 13713
## INFO [2023-06-22 12:33:43]  [5617] 13714 13715 13716 13717 13718 13719 13720 13721 13722 13723 13724 13725
## INFO [2023-06-22 12:33:43]  [5629] 13726 13727 13728 13729 13730 13731 13732 13733 13734 13735 13736 13737
## INFO [2023-06-22 12:33:43]  [5641] 13738 13739 13740 13741 13742 13743 13744 13745 13746 13747 13748 13749
## INFO [2023-06-22 12:33:43]  [5653] 13750 13751 13752 13753 13754 13755 13756 13757 13758 13759 13760 13761
## INFO [2023-06-22 12:33:43]  [5665] 13762 13763 13764 13765 13766 13767 13768 13769 13770 13771 13772 13773
## INFO [2023-06-22 12:33:43]  [5677] 13774 13775 13776 13777 13778 13779 13780 13781 13782 13783 13784 13785
## INFO [2023-06-22 12:33:43]  [5689] 13786 13787 13788 13789 13790 13791 13792 13793 13794 13795 13796 13797
## INFO [2023-06-22 12:33:43]  [5701] 13798 13799 13800 13801 13802 13803 13804 13805 13806 13807 13808 13809
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## INFO [2023-06-22 12:33:43]  [5725] 13822 13823 13824 13825 13826 13827 13828 13829 13830 13831 13832 13833
## INFO [2023-06-22 12:33:43]  [5737] 13834 13835 13836 13837 13838 13839 13840 13841 13842 13843 13844 13845
## INFO [2023-06-22 12:33:43]  [5749] 13846 13847 13848 13849 13850 13851 13852 13853 13854 13855 13856 13857
## INFO [2023-06-22 12:33:43]  [5761] 13858 13859 13860 13861 13862 13863 13864 13865 13866 13867 13868 13869
## INFO [2023-06-22 12:33:43]  [5773] 13870 13871 13872 13873 13874 13875 13876 13877 13878 13879 13880 13881
## INFO [2023-06-22 12:33:43]  [5785] 13882 13883 13884 13885 13886 13887 13888 13889 13890 13891 13892 13893
## INFO [2023-06-22 12:33:43]  [5797] 13894 13895 13896 13897 13898 13899 13900 13901 13902 13903 13904 13905
## INFO [2023-06-22 12:33:43]  [5809] 13906 13907 13908 13909 13910 13911 13912 13913 13914 13915 13916 13917
## INFO [2023-06-22 12:33:43]  [5821] 13918 13919 13920 13921 13922 13923 13924 13925 13926 13927 13928 13929
## INFO [2023-06-22 12:33:43]  [5833] 13930 13931 13932 13933 13934 13935 13936 13937 13938 13939 13940 13941
## INFO [2023-06-22 12:33:43]  [5845] 13942 13943 13944 13945 13946 13947 13948 13949 13950 13951 13952 13953
## INFO [2023-06-22 12:33:43]  [5857] 13954 13955 13956 13957 13958 13959 13960 13961 13962 13963 13964 13965
## INFO [2023-06-22 12:33:43]  [5869] 13966 13967 13968 13969 13970 13971 13972 13973 13974 13975 13976 13977
## INFO [2023-06-22 12:33:43]  [5881] 13978 13979 13980 13981 13982 13983 13984 13985 13986 13987 13988 13989
## INFO [2023-06-22 12:33:43]  [5893] 13990 13991 13992 13993 13994 13995 13996 13997 13998 13999 14000 14001
## INFO [2023-06-22 12:33:43]  [5905] 14002 14003 14004 14005 14006 14007 14008 14009 14010 14011 14012 14013
## INFO [2023-06-22 12:33:43]  [5917] 14014 14015 14016 14017 14018 14019 14020 14021 14022 14023 14024 14025
## INFO [2023-06-22 12:33:43]  [5929] 14026 14027 14028 14029 14030 14031 14032 14033 14034 14035 14036 14037
## INFO [2023-06-22 12:33:43]  [5941] 14038 14039 14040 14041 14042 14043 14044 14045 14046 14047 14048 14049
## INFO [2023-06-22 12:33:43]  [5953] 14050 14051 14052 14053 14054 14055 14056 14057 14058 14059 14060 14061
## INFO [2023-06-22 12:33:43]  [5965] 14062 14063 14064 14065 14066 14067 14068 14069 14070 14071 14072 14073
## INFO [2023-06-22 12:33:43]  [5977] 14074 14075 14076 14077 14078 14079 14080 14081 14082 14083 14084 14085
## INFO [2023-06-22 12:33:43]  [5989] 14086 14087 14088 14089 14090 14091 14092 14093 14094 14095 14096 14097
## INFO [2023-06-22 12:33:43]  [6001] 14098 14099 14100 14101 14102 14103 14104 14105 14106 14107 14108 14109
## INFO [2023-06-22 12:33:43]  [6013] 14110 14111 14112 14113 14114 14115 14116 14117 14118 14119 14120 14121
## INFO [2023-06-22 12:33:43]  [6025] 14122 14123 14124 14125 14126 14127 14128 14129 14130 14131 14132 14133
## INFO [2023-06-22 12:33:43]  [6037] 14134 14135 14136 14137 14138 14139 14140 14141 14142 14143 14144 14145
## INFO [2023-06-22 12:33:43]  [6049] 14146 14147 14148 14149 14150 14151 14152 14153 14154 14155 14156 14157
## INFO [2023-06-22 12:33:43]  [6061] 14158 14159 14160 14161 14162 14163 14164 14165 14166 14167 14168 14169
## INFO [2023-06-22 12:33:43]  [6073] 14170 14171 14172 14173 14174 14175 14176 14177 14178 14179 14180 14181
## INFO [2023-06-22 12:33:43]  [6085] 14182 14183 14184 14185 14186 14187 14188 14189 14190 14191 14192 14193
## INFO [2023-06-22 12:33:43]  [6097] 14194 14195 14196 14197 14198 14199 14200 14201 14202 14203 14204 14205
## INFO [2023-06-22 12:33:43]  [6109] 14206 14207 14208 14209 14210 14211 14212 14213 14214 14215 14216 14217
## INFO [2023-06-22 12:33:43]  [6121] 14218 14219 14220 14221 14222 14223 14224 14225 14226 14227 14228 14229
## INFO [2023-06-22 12:33:43]  [6133] 14230 14231 14232 14233 14234 14235 14236 14237 14238 14239 14240 14241
## INFO [2023-06-22 12:33:43]  [6145] 14242 14243 14244 14245 14246 14247 14248 14249 14250 14251 14252 14253
## INFO [2023-06-22 12:33:43]  [6157] 14254 14255 14256 14257 14258 14259 14260 14261 14262 14263 14264 14265
## INFO [2023-06-22 12:33:43]  [6169] 14266 14267 14268 14269 14270 14271 14272 14273 14274 14275 14276 14277
## INFO [2023-06-22 12:33:43]  [6181] 14278 14279 14280 14281 14282 14283 14284 14285 14286 14287 14288 14289
## INFO [2023-06-22 12:33:43]  [6193] 14290 14291 14292 14293 14294 14295 14296 14297 14298 14299 14300 14301
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## INFO [2023-06-22 12:33:43]  [8053] 16150 16151 16152 16153 16154 16155 16156 16157 16158 16159 16160 16161
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## INFO [2023-06-22 12:33:43]  [8185] 16282 16283 16284 16285 16286 16287 16288 16289 16290 16291 16292 16293
## INFO [2023-06-22 12:33:43]  [8197] 16294 16295 16296 16297 16298 16299 16300 16301 16302 16303 16304 16305
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## INFO [2023-06-22 12:33:43]  [8245] 16342 16343 16344 16345 16346 16347 16348 16349 16350 16351 16352 16353
## INFO [2023-06-22 12:33:43]  [8257] 16354 16355 16356 16357 16358 16359 16360 16361 16362 16363 16364 16365
## INFO [2023-06-22 12:33:43]  [8269] 16366 16367 16368 16369 16370 16371 16372 16373 16374 16375 16376 16377
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## INFO [2023-06-22 12:33:43]  [8293] 16390 16391 16392 16393 16394 16395 16396 16397 16398 16399 16400 16401
## INFO [2023-06-22 12:33:43]  [8305] 16402 16403 16404 16405 16406 16407 16408 16409 16410 16411 16412 16413
## INFO [2023-06-22 12:33:43]  [8317] 16414 16415 16416 16417 16418 16419 16420 16421 16422 16423 16424 16425
## INFO [2023-06-22 12:33:43]  [8329] 16426 16427 16428 16429 16430 16431 16432 16433 16434 16435 16436 16437
## INFO [2023-06-22 12:33:43]  [8341] 16438 16439 16440 16441 16442 16443 16444 16445 16446 16447 16448 16449
## INFO [2023-06-22 12:33:43]  [8353] 16450 16451 16452 16453 16454 16455 16456 16457 16458 16459 16460 16461
## INFO [2023-06-22 12:33:43]  [8365] 16462 16463 16464 16465 16466 16467 16468 16469 16470 16471 16472 16473
## INFO [2023-06-22 12:33:43]  [8377] 16474 16475 16476 16477 16478 16479 16480 16481 16482 16483 16484 16485
## INFO [2023-06-22 12:33:43]  [8389] 16486 16487 16488 16489 16490 16491 16492 16493 16494 16495 16496 16497
## INFO [2023-06-22 12:33:43]  [8401] 16498 16499 16500 16501 16502 16503 16504 16505 16506 16507 16508 16509
## INFO [2023-06-22 12:33:43]  [8413] 16510 16511 16512 16513 16514 16515 16516 16517 16518 16519 16520 16521
## INFO [2023-06-22 12:33:43]  [8425] 16522 16523 16524 16525 16526 16527 16528 16529 16530 16531 16532 16533
## INFO [2023-06-22 12:33:43]  [8437] 16534 16535 16536 16537 16538 16539 16540 16541 16542 16543 16544 16545
## INFO [2023-06-22 12:33:43]  [8449] 16546 16547 16548 16549 16550 16551 16552 16553 16554 16555 16556 16557
## INFO [2023-06-22 12:33:43]  [8461] 16558 16559 16560 16561 16562 16563 16564 16565 16566 16567 16568 16569
## INFO [2023-06-22 12:33:43]  [8473] 16570 16571 16572 16573 16574 16575 16576 16577 16578 16579 16580 16581
## INFO [2023-06-22 12:33:43]  [8485] 16582 16583 16584 16585 16586 16587 16588 16589 16590 16591 16592 16593
## INFO [2023-06-22 12:33:43]  [8497] 16594 16595 16596 16597 16598 16599 16600 16601 16602 16603 16604 16605
## INFO [2023-06-22 12:33:43]  [8509] 16606 16607 16608 16609 16610 16611 16612 16613 16614 16615 16616 16617
## INFO [2023-06-22 12:33:43]  [8521] 16618 16619 16620 16621 16622 16623 16624 16625 16626 16627 16628 16629
## INFO [2023-06-22 12:33:43]  [8533] 16630 16631 16632 16633 16634 16635 16636 16637 16638 16639 16640 16641
## INFO [2023-06-22 12:33:43]  [8545] 16642 16643 16644 16645 16646 16647 16648 16649 16650 16651 16652 16653
## INFO [2023-06-22 12:33:43]  [8557] 16654 16655 16656 16657 16658 16659 16660 16661 16662 16663 16664 16665
## INFO [2023-06-22 12:33:43]  [8569] 16666 16667 16668 16669 16670 16671 16672 16673 16674 16675 16676 16677
## INFO [2023-06-22 12:33:43]  [8581] 16678 16679 16680 16681 16682 16683 16684 16685 16686 16687 16688 16689
## INFO [2023-06-22 12:33:43]  [8593] 16690 16691 16692 16693 16694 16695 16696 16697 16698 16699 16700 16701
## INFO [2023-06-22 12:33:43]  [8605] 16702 16703 16704 16705 16706 16707 16708 16709 16710 16711 16712 16713
## INFO [2023-06-22 12:33:43]  [8617] 16714 16715 16716 16717 16718 16719 16720 16721 16722 16723 16724 16725
## INFO [2023-06-22 12:33:43]  [8629] 16726 16727 16728 16729 16730 16731 16732 16733 16734 16735 16736 16737
## INFO [2023-06-22 12:33:43]  [8641] 16738 16739 16740 16741 16742 16743 16744 16745 16746 16747 16748 16749
## INFO [2023-06-22 12:33:43]  [8653] 16750 16751 16752 16753 16754 16755 16756 16757 16758 16759 16760 16761
## INFO [2023-06-22 12:33:43]  [8665] 16762 16763 16764 16765 16766 16767 16768 16769 16770 16771 16772 16773
## INFO [2023-06-22 12:33:43]  [8677] 16774 16775 16776 16777 16778 16779 16780 16781 16782 16783 16784 16785
## INFO [2023-06-22 12:33:43]  [8689] 16786 16787 16788 16789 16790 16791 16792 16793 16794 16795 16796 16797
## INFO [2023-06-22 12:33:43]  [8701] 16798 16799 16800 16801 16802 16803 16804 16805 16806 16807 16808 16809
## INFO [2023-06-22 12:33:43]  [8713] 16810 16811 16812 16813 16814 16815 16816 16817 16818 16819 16820 16821
## INFO [2023-06-22 12:33:43]  [8725] 16822 16823 16824 16825 16826 16827 16828 16829 16830 16831 16832 16833
## INFO [2023-06-22 12:33:43]  [8737] 16834 16835 16836 16837 16838 16839 16840 16841 16842 16843 16844 16845
## INFO [2023-06-22 12:33:43]  [8749] 16846 16847 16848 16849 16850 16851 16852 16853 16854 16855 16856 16857
## INFO [2023-06-22 12:33:43]  [8761] 16858 16859 16860 16861 16862 16863 16864 16865 16866 16867 16868 16869
## INFO [2023-06-22 12:33:43]  [8773] 16870 16871 16872 16873 16874 16875 16876 16877 16878 16879 16880 16881
## INFO [2023-06-22 12:33:43]  [8785] 16882 16883 16884 16885 16886 16887 16888 16889 16890 16891 16892 16893
## INFO [2023-06-22 12:33:43]  [8797] 16894 16895 16896 16897 16898 16899 16900 16901 16902 16903 16904 16905
## INFO [2023-06-22 12:33:43]  [8809] 16906 16907 16908 16909 16910 16911 16912 16913 16914 16915 16916 16917
## INFO [2023-06-22 12:33:43]  [8821] 16918 16919 16920 16921 16922 16923 16924 16925 16926 16927 16928 16929
## INFO [2023-06-22 12:33:43]  [8833] 16930 16931 16932 16933 16934 16935 16936 16937 16938 16939 16940 16941
## INFO [2023-06-22 12:33:43]  [8845] 16942 16943 16944 16945 16946 16947 16948 16949 16950 16951 16952 16953
## INFO [2023-06-22 12:33:43]  [8857] 16954 16955 16956 16957 16958 16959 16960 16961 16962 16963 16964 16965
## INFO [2023-06-22 12:33:43]  [8869] 16966 16967 16968 16969 16970 16971 16972 16973 16974 16975 16976 16977
## INFO [2023-06-22 12:33:43]  [8881] 16978 16979 16980 16981 16982 16983 16984 16985 16986 16987 16988 16989
## INFO [2023-06-22 12:33:43]  [8893] 16990 16991 16992 16993 16994 16995 16996 16997 16998 16999 17000 17001
## INFO [2023-06-22 12:33:43]  [8905] 17002 17003 17004 17005 17006 17007 17008 17009 17010 17011 17012 17013
## INFO [2023-06-22 12:33:43]  [8917] 17014 17015 17016 17017 17018 17019 17020 17021 17022 17023 17024 17025
## INFO [2023-06-22 12:33:43]  [8929] 17026 17027 17028 17029 17030 17031 17032 17033 17034 17035 17036 17037
## INFO [2023-06-22 12:33:43]  [8941] 17038 17039 17040 17041 17042 17043 17044 17045 17046 17047 17048 17049
## INFO [2023-06-22 12:33:43]  [8953] 17050 17051 17052 17053 17054 17055 17056 17057 17058 17059 17060 17061
## INFO [2023-06-22 12:33:43]  [8965] 17062 17063 17064 17065 17066 17067 17068 17069 17070 17071 17072 17073
## INFO [2023-06-22 12:33:43]  [8977] 17074 17075 17076 17077 17078 17079 17080 17081 17082 17083 17084 17085
## INFO [2023-06-22 12:33:43]  [8989] 17086 17087 17088 17089 17090 17091 17092 17093 17094 17095 17096 17097
## INFO [2023-06-22 12:33:43]  [9001] 17098 17099 17100 17101 17102 17103 17104 17105 17106 17107 17108 17109
## INFO [2023-06-22 12:33:43]  [9013] 17110 17111 17112 17113 17114 17115 17116 17117 17118 17119 17120 17121
## INFO [2023-06-22 12:33:43]  [9025] 17122 17123 17124 17125 17126 17127 17128 17129 17130 17131 17132 17133
## INFO [2023-06-22 12:33:43]  [9037] 17134 17135 17136 17137 17138 17139 17140 17141 17142 17143 17144 17145
## INFO [2023-06-22 12:33:43]  [9049] 17146 17147 17148 17149 17150 17151 17152 17153 17154 17155 17156 17157
## INFO [2023-06-22 12:33:43]  [9061] 17158 17159 17160 17161 17162 17163 17164 17165 17166 17167 17168 17169
## INFO [2023-06-22 12:33:43]  [9073] 17170 17171 17172 17173 17174 17175 17176 17177 17178 17179 17180 17181
## INFO [2023-06-22 12:33:43]  [9085] 17182 17183 17184 17185 17186 17187 17188 17189 17190 17191 17192 17193
## INFO [2023-06-22 12:33:43]  [9097] 17194 17195 17196 17197 17198 17199 17200 17201 17202 17203 17204 17205
## INFO [2023-06-22 12:33:43]  [9109] 17206 17207 17208 17209 17210 17211 17212 17213 17214 17215 17216 17217
## INFO [2023-06-22 12:33:43]  [9121] 17218 17219 17220 17221 17222 17223 17224 17225 17226 17227 17228 17229
## INFO [2023-06-22 12:33:43]  [9133] 17230 17231 17232 17233 17234 17235 17236 17237 17238 17239 17240 17241
## INFO [2023-06-22 12:33:43]  [9145] 17242 17243 17244 17245 17246 17247 17248 17249 17250 17251 17252 17253
## INFO [2023-06-22 12:33:43]  [9157] 17254 17255 17256 17257 17258 17259 17260 17261 17262 17263 17264 17265
## INFO [2023-06-22 12:33:43]  [9169] 17266 17267 17268 17269 17270 17271 17272 17273 17274 17275 17276 17277
## INFO [2023-06-22 12:33:43]  [9181] 17278 17279 17280 17281 17282 17283 17284 17285 17286 17287 17288 17289
## INFO [2023-06-22 12:33:43]  [9193] 17290 17291 17292 17293 17294 17295 17296 17297 17298 17299 17300 17301
## INFO [2023-06-22 12:33:43]  [9205] 17302 17303 17304 17305 17306 17307 17308 17309 17310 17311 17312 17313
## INFO [2023-06-22 12:33:43]  [9217] 17314 17315 17316 17317 17318 17319 17320 17321 17322 17323 17324 17325
## INFO [2023-06-22 12:33:43]  [9229] 17326 17327 17328 17329 17330 17331 17332 17333 17334 17335 17336 17337
## INFO [2023-06-22 12:33:43]  [9241] 17338 17339 17340 17341 17342 17343 17344 17345 17346 17347 17348 17349
## INFO [2023-06-22 12:33:43]  [9253] 17350 17351 17352 17353 17354 17355 17356 17357 17358 17359 17360 17361
## INFO [2023-06-22 12:33:43]  [9265] 17362 17363 17364 17365 17366 17367 17368 17369 17370 17371 17372 17373
## INFO [2023-06-22 12:33:43]  [9277] 17374 17375 17376 17377 17378 17379 17380 17381 17382 17383 17384 17385
## INFO [2023-06-22 12:33:43]  [9289] 17386 17387 17388 17389 17390 17391 17392 17393 17394 17395 17396 17397
## INFO [2023-06-22 12:33:43]  [9301] 17398 17399 17400 17401 17402 17403 17404 17405 17406 17407 17408 17409
## INFO [2023-06-22 12:33:43]  [9313] 17410 17411 17412 17413 17414 17415 17416 17417 17418 17419 17420 17421
## INFO [2023-06-22 12:33:43]  [9325] 17422 17423 17424 17425 17426 17427 17428 17429 17430 17431 17432 17433
## INFO [2023-06-22 12:33:43]  [9337] 17434 17435 17436 17437 17438 17439 17440 17441 17442 17443 17444 17445
## INFO [2023-06-22 12:33:43]  [9349] 17446 17447 17448 17449 17450 17451 17452 17453 17454 17455 17456 17457
## INFO [2023-06-22 12:33:43]  [9361] 17458 17459 17460 17461 17462 17463 17464 17465 17466 17467 17468 17469
## INFO [2023-06-22 12:33:43]  [9373] 17470 17471 17472 17473 17474 17475 17476 17477 17478 17479 17480 17481
## INFO [2023-06-22 12:33:43]  [9385] 17482 17483 17484 17485 17486 17487 17488 17489 17490 17491 17492 17493
## INFO [2023-06-22 12:33:43]  [9397] 17494 17495 17496 17497 17498 17499 17500 17501 17502 17503 17504 17505
## INFO [2023-06-22 12:33:43]  [9409] 17506 17507 17508 17509 17510 17511 17512 17513 17514 17515 17516 17517
## INFO [2023-06-22 12:33:43]  [9421] 17518 17519 17520 17521 17522 17523 17524 17525 17526 17527 17528 17529
## INFO [2023-06-22 12:33:43]  [9433] 17530 17531 17532 17533 17534 17535 17536 17537 17538 17539 17540 17541
## INFO [2023-06-22 12:33:43]  [9445] 17542 17543 17544 17545 17546 17547 17548 17549 17550 17551 17552 17553
## INFO [2023-06-22 12:33:43]  [9457] 17554 17555 17556 17557 17558 17559 17560 17561 17562 17563 17564 17565
## INFO [2023-06-22 12:33:43]  [9469] 17566 17567 17568 17569 17570 17571 17572 17573 17574 17575 17576 17577
## INFO [2023-06-22 12:33:43]  [9481] 17578 17579 17580 17581 17582 17583 17584 17585 17586 17587 17588 17589
## INFO [2023-06-22 12:33:43]  [9493] 17590 17591 17592 17593 17594 17595 17596 17597 17598 17599 17600 17601
## INFO [2023-06-22 12:33:43]  [9505] 17602 17603 17604 17605 17606 17607 17608 17609 17610 17611 17612 17613
## INFO [2023-06-22 12:33:43]  [9517] 17614 17615 17616 17617 17618 17619 17620 17621 17622 17623 17624 17625
## INFO [2023-06-22 12:33:43]  [9529] 17626 17627 17628 17629 17630 17631 17632 17633 17634 17635 17636 17637
## INFO [2023-06-22 12:33:43]  [9541] 17638 17639 17640 17641 17642 17643 17644 17645 17646 17647 17648 17649
## INFO [2023-06-22 12:33:43]  [9553] 17650 17651 17652 17653 17654 17655 17656 17657 17658 17659 17660 17661
## INFO [2023-06-22 12:33:43]  [9565] 17662 17663 17664 17665 17666 17667 17668 17669 17670 17671 17672 17673
## INFO [2023-06-22 12:33:43]  [9577] 17674 17675 17676 17677 17678 17679 17680 17681 17682 17683 17684 17685
## INFO [2023-06-22 12:33:43]  [9589] 17686 17687 17688 17689 17690 17691 17692 17693 17694 17695 17696 17697
## INFO [2023-06-22 12:33:43]  [9601] 17698 17699 17700 17701 17702 17703 17704 17705 17706 17707 17708 17709
## INFO [2023-06-22 12:33:43]  [9613] 17710 17711 17712 17713 17714 17715 17716 17717 17718 17719 17720 17721
## INFO [2023-06-22 12:33:43]  [9625] 17722 17723 17724 17725 17726 17727 17728 17729 17730 17731 17732 17733
## INFO [2023-06-22 12:33:43]  [9637] 17734 17735 17736 17737 17738 17739 17740 17741 17742 17743 17744 17745
## INFO [2023-06-22 12:33:43]  [9649] 17746 17747 17748 17749 17750 17751 17752 17753 17754 17755 17756 17757
## INFO [2023-06-22 12:33:43]  [9661] 17758 17759 17760 17761 17762 17763 17764 17765 17766 17767 17768 17769
## INFO [2023-06-22 12:33:43]  [9673] 17770 17771 17772 17773 17774 17775 17776 17777 17778 17779 17780 17781
## INFO [2023-06-22 12:33:43]  [9685] 17782 17783 17784 17785 17786 17787 17788 17789 17790 17791 17792 17793
## INFO [2023-06-22 12:33:43]  [9697] 17794 17795 17796 17797 17798 17799 17800 17801 17802 17803 17804 17805
## INFO [2023-06-22 12:33:43]  [9709] 17806 17807 17808 17809 17810 17811 17812 17813 17814 17815 17816 17817
## INFO [2023-06-22 12:33:43]  [9721] 17818 17819 17820 17821 17822 17823 17824 17825 17826 17827 17828 17829
## INFO [2023-06-22 12:33:43]  [9733] 17830 17831 17832 17833 17834 17835 17836 17837 17838 17839 17840 17841
## INFO [2023-06-22 12:33:43]  [9745] 17842 17843 17844 17845 17846 17847 17848 17849 17850 17851 17852 17853
## INFO [2023-06-22 12:33:43]  [9757] 17854 17855 17856 17857 17858 17859 17860 17861 17862 17863 17864 17865
## INFO [2023-06-22 12:33:43]  [9769] 17866 17867 17868 17869 17870 17871 17872 17873 17874 17875 17876 17877
## INFO [2023-06-22 12:33:43]  [9781] 17878 17879 17880 17881 17882 17883 17884 17885 17886 17887 17888 17889
## INFO [2023-06-22 12:33:43]  [9793] 17890 17891 17892 17893 17894 17895 17896 17897 17898 17899 17900 17901
## INFO [2023-06-22 12:33:43]  [9805] 17902 17903 17904 17905 17906 17907 17908 17909 17910 17911 17912 17913
## INFO [2023-06-22 12:33:43]  [9817] 17914 17915 17916 17917 17918 17919 17920 17921 17922 17923 17924 17925
## INFO [2023-06-22 12:33:43]  [9829] 17926 17927 17928 17929 17930 17931 17932 17933 17934 17935 17936 17937
## INFO [2023-06-22 12:33:43]  [9841] 17938 17939 17940 17941 17942 17943 17944 17945 17946 17947 17948 17949
## INFO [2023-06-22 12:33:43]  [9853] 17950 17951 17952 17953 17954 17955 17956 17957 17958 17959 17960 17961
## INFO [2023-06-22 12:33:43]  [9865] 17962 17963 17964 17965 17966 17967 17968 17969 17970 17971 17972 17973
## INFO [2023-06-22 12:33:43]  [9877] 17974 17975 17976 17977 17978 17979 17980 17981 17982 17983 17984 17985
## INFO [2023-06-22 12:33:43]  [9889] 17986 17987 17988 17989 17990 17991 17992 17993 17994 17995 17996 17997
## INFO [2023-06-22 12:33:43]  [9901] 17998 17999 18000 18001 18002 18003 18004 18005 18006 18007 18008 18009
## INFO [2023-06-22 12:33:43]  [9913] 18010 18011 18012 18013 18014 18015 18016 18017 18018 18019 18020 18021
## INFO [2023-06-22 12:33:43]  [9925] 18022 18023 18024 18025 18026 18027 18028 18029 18030 18031 18032 18033
## INFO [2023-06-22 12:33:43]  [9937] 18034 18035 18036 18037 18038 18039 18040 18041 18042 18043 18044 18045
## INFO [2023-06-22 12:33:43]  [9949] 18046 18047 18048 18049 18050 18051 18052 18053 18054 18055 18056 18057
## INFO [2023-06-22 12:33:43]  [9961] 18058 18059 18060 18061 18062 18063 18064 18065 18066 18067 18068 18069
## INFO [2023-06-22 12:33:43]  [9973] 18070 18071 18072 18073 18074 18075 18076 18077 18078 18079 18080 18081
## INFO [2023-06-22 12:33:43]  [9985] 18082 18083 18084 18085 18086 18087 18088 18089 18090 18091 18092 18093
## INFO [2023-06-22 12:33:43]  [9997] 18094 18095 18096 18097 18098 18099 18100 18101 18102 18103 18104 18105
## INFO [2023-06-22 12:33:43] [10009] 18106 18107 18108 18109 18110 18111 18112 18113 18114 18115 18116 18117
## INFO [2023-06-22 12:33:43] [10021] 18118 18119 18120 18121 18122 18123 18124 18125 18126 18127 18128 18129
## INFO [2023-06-22 12:33:43] [10033] 18130 18131 18132 18133 18134 18135 18136 18137 18138 18139 18140 18141
## INFO [2023-06-22 12:33:43] [10045] 18142 18143 18144 18145 18146 18147 18148 18149 18150 18151 18152 18153
## INFO [2023-06-22 12:33:43] [10057] 18154 18155 18156 18157 18158 18159 18160 18161 18162 18163 18164 18165
## INFO [2023-06-22 12:33:43] [10069] 18166 18167 18168 18169 18170 18171 18172 18173 18174 18175 18176 18177
## INFO [2023-06-22 12:33:43] [10081] 18178 18179 18180 18181 18182 18183 18184 18185 18186 18187 18188 18189
## INFO [2023-06-22 12:33:43] [10093] 18190 18191 18192 18193 18194 18195 18196 18197 18198 18199 18200 18201
## INFO [2023-06-22 12:33:43] [10105] 18202 18203 18204 18205 18206 18207 18208 18209 18210 18211 18212 18213
## INFO [2023-06-22 12:33:43] [10117] 18214 18215 18216 18217 18218 18219 18220 18221 18222 18223 18224 18225
## INFO [2023-06-22 12:33:43] [10129] 18226 18227 18228 18229 18230 18231 18232 18233 18234 18235 18236 18237
## INFO [2023-06-22 12:33:43] [10141] 18238 18239 18240 18241 18242 18243 18244 18245 18246 18247 18248 18249
## INFO [2023-06-22 12:33:43] [10153] 18250 18251 18252 18253 18254 18255 18256 18257 18258 18259 18260 18261
## INFO [2023-06-22 12:33:43] [10165] 18262 18263 18264 18265 18266 18267 18268 18269 18270 18271 18272 18273
## INFO [2023-06-22 12:33:43] [10177] 18274 18275 18276 18277 18278 18279 18280 18281 18282 18283 18284 18285
## INFO [2023-06-22 12:33:43] [10189] 18286 18287 18288 18289 18290 18291 18292 18293 18294 18295 18296 18297
## INFO [2023-06-22 12:33:43] [10201] 18298 18299 18300 18301 18302 18303 18304 18305 18306 18307 18308 18309
## INFO [2023-06-22 12:33:43] [10213] 18310 18311 18312 18313 18314 18315 18316 18317 18318 18319 18320 18321
## INFO [2023-06-22 12:33:43] [10225] 18322 18323 18324 18325 18326 18327 18328 18329 18330 18331 18332 18333
## INFO [2023-06-22 12:33:43] [10237] 18334 18335 18336 18337 18338 18339 18340 18341 18342 18343 18344 18345
## INFO [2023-06-22 12:33:43] [10249] 18346 18347 18348 18349 18350 18351 18352 18353 18354 18355 18356 18357
## INFO [2023-06-22 12:33:43] [10261] 18358 18359 18360 18361 18362 18363 18364 18365 18366 18367 18368 18369
## INFO [2023-06-22 12:33:43] [10273] 18370 18371 18372 18373 18374 18375 18376 18377 18378 18379 18380 18381
## INFO [2023-06-22 12:33:43] [10285] 18382 18383 18384 18385 18386 18387 18388 18389 18390 18391 18392 18393
## INFO [2023-06-22 12:33:43] [10297] 18394 18395 18396 18397 18398 18399 18400 18401 18402 18403 18404 18405
## INFO [2023-06-22 12:33:43] [10309] 18406 18407 18408 18409 18410 18411 18412 18413 18414 18415 18416 18417
## INFO [2023-06-22 12:33:43] [10321] 18418 18419 18420 18421 18422 18423 18424 18425 18426 18427 18428 18429
## INFO [2023-06-22 12:33:43] [10333] 18430 18431 18432 18433 18434 18435 18436 18437 18438 18439 18440 18441
## INFO [2023-06-22 12:33:43] [10345] 18442 18443 18444 18445 18446 18447 18448 18449 18450 18451 18452 18453
## INFO [2023-06-22 12:33:43] [10357] 18454 18455 18456 18457 18458 18459 18460 18461 18462 18463 18464 18465
## INFO [2023-06-22 12:33:43] [10369] 18466 18467 18468 18469 18470 18471 18472 18473 18474 18475 18476 18477
## INFO [2023-06-22 12:33:43] [10381] 18478 18479 18480 18481 18482 18483 18484 18485 18486 18487 18488 18489
## INFO [2023-06-22 12:33:43] [10393] 18490 18491 18492 18493 18494 18495 18496 18497 18498 18499 18500 18501
## INFO [2023-06-22 12:33:43] [10405] 18502 18503 18504 18505 18506 18507 18508 18509 18510 18511 18512 18513
## INFO [2023-06-22 12:33:43] [10417] 18514 18515 18516 18517 18518 18519 18520 18521 18522 18523 18524 18525
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## INFO [2023-06-22 12:33:43] [11533] 19630 19631 19632 19633 19634 19635 19636 19637 19638 19639 19640 19641
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## INFO [2023-06-22 12:33:43] [11557] 19654 19655 19656 19657 19658 19659 19660 19661 19662 19663 19664 19665
## INFO [2023-06-22 12:33:43] [11569] 19666 19667 19668 19669 19670 19671 19672 19673 19674 19675 19676 19677
## INFO [2023-06-22 12:33:43] [11581] 19678 19679 19680 19681 19682 19683 19684 19685 19686 19687 19688 19689
## INFO [2023-06-22 12:33:43] [11593] 19690 19691 19692 19693 19694 19695 19696 19697 19698 19699 19700 19701
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## INFO [2023-06-22 12:33:43] [11653] 19750 19751 19752 19753 19754 19755 19756 19757 19758 19759 19760 19761
## INFO [2023-06-22 12:33:43] [11665] 19762 19763 19764 19765 19766 19767 19768 19769 19770 19771 19772 19773
## INFO [2023-06-22 12:33:43] [11677] 19774 19775 19776 19777 19778 19779 19780 19781 19782 19783 19784 19785
## INFO [2023-06-22 12:33:43] [11689] 19786 19787 19788 19789 19790 19791 19792 19793 19794 19795 19796 19797
## INFO [2023-06-22 12:33:43] [11701] 19798 19799 19800 19801 19802 19803 19804 19805 19806 19807 19808 19809
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## INFO [2023-06-22 12:33:43] [11737] 19834 19835 19836 19837 19838 19839 19840 19841 19842 19843 19844 19845
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## INFO [2023-06-22 12:33:43] [12097] 20194 20195 20196 20197 20198 20199 20200 20201 20202 20203 20204 20205
## INFO [2023-06-22 12:33:43] [12109] 20206 20207 20208 20209 20210 20211 20212 20213 20214 20215 20216 20217
## INFO [2023-06-22 12:33:43] [12121] 20218 20219 20220 20221 20222 20223 20224 20225 20226 20227 20228 20229
## INFO [2023-06-22 12:33:43] [12133] 20230 20231 20232 20233 20234 20235 20236 20237 20238 20239 20240 20241
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## INFO [2023-06-22 12:33:43] [12157] 20254 20255 20256 20257 20258 20259 20260 20261 20262 20263 20264 20265
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## INFO [2023-06-22 12:33:43] [12193] 20290 20291 20292 20293 20294 20295 20296 20297 20298 20299 20300 20301
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## INFO [2023-06-22 12:33:43] [12229] 20326 20327 20328 20329 20330 20331 20332 20333 20334 20335 20336 20337
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## INFO [2023-06-22 12:33:43] [12253] 20350 20351 20352 20353 20354 20355 20356 20357 20358 20359 20360 20361
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## INFO [2023-06-22 12:33:43] [12301] 20398 20399 20400 20401 20402 20403 20404 20405 20406 20407 20408 20409
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## INFO [2023-06-22 12:33:43] [12409] 20506 20507 20508 20509 20510 20511 20512 20513 20514 20515 20516 20517
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## INFO [2023-06-22 12:33:43] [12529] 20626 20627 20628 20629 20630 20631 20632 20633 20634 20635 20636 20637
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## INFO [2023-06-22 12:33:43] [13873] 21970 21971 21972 21973 21974 21975 21976 21977 21978 21979 21980 21981
## INFO [2023-06-22 12:33:43] [13885] 21982 21983 21984 21985 21986 21987 21988 21989 21990 21991 21992 21993
## INFO [2023-06-22 12:33:43] [13897] 21994 21995 21996 21997 21998 21999 22000 22001 22002 22003 22004 22005
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## INFO [2023-06-22 12:33:43] [19681] 27778 27779 27780 27781 27782 27783 27784 27785 27786 27787 27788 27789
## INFO [2023-06-22 12:33:43] [19693] 27790 27791 27792 27793 27794 27795 27796 27797 27798 27799 27800 27801
## INFO [2023-06-22 12:33:43] [19705] 27802 27803 27804 27805 27806 27807 27808 27809 27810 27811 27812 27813
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## INFO [2023-06-22 12:33:43] [19753] 27850 27851 27852 27853 27854 27855 27856 27857 27858 27859 27860 27861
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## INFO [2023-06-22 12:33:43] [19777] 27874 27875 27876 27877 27878 27879 27880 27881 27882 27883 27884 27885
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## INFO [2023-06-22 12:33:43] [19861] 27958 27959 27960 27961 27962 27963 27964 27965 27966 27967 27968 27969
## INFO [2023-06-22 12:33:43] [19873] 27970 27971 27972 27973 27974 27975 27976 27977 27978 27979 27980 27981
## INFO [2023-06-22 12:33:43] [19885] 27982 27983 27984 27985 27986 27987 27988 27989 27990 27991 27992 27993
## INFO [2023-06-22 12:33:43] [19897] 27994 27995 27996 27997 27998 27999 28000 28001 28002 28003 28004 28005
## INFO [2023-06-22 12:33:43] [19909] 28006 28007 28008 28009 28010 28011 28012 28013 28014 28015 28016 28017
## INFO [2023-06-22 12:33:43] [19921] 28018 28019 28020 28021 28022 28023 28024 28025 28026 28027 28028 28029
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## INFO [2023-06-22 12:33:43] [19957] 28054 28055 28056 28057 28058 28059 28060 28061 28062 28063 28064 28065
## INFO [2023-06-22 12:33:43] [19969] 28066 28067 28068 28069 28070 28071 28072 28073 28074 28075 28076 28077
## INFO [2023-06-22 12:33:43] [19981] 28078 28079 28080 28081 28082 28083 28084 28085 28086 28087 28088 28089
## INFO [2023-06-22 12:33:43] [19993] 28090 28091 28092 28093 28094 28095 28096 28097 28098 28099 28100 28101
## INFO [2023-06-22 12:33:43] [20005] 28102 28103 28104 28105 28106 28107 28108 28109 28110 28111 28112 28113
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## INFO [2023-06-22 12:33:43] [20089] 28186 28187 28188 28189 28190 28191 28192 28193 28194 28195 28196 28197
## INFO [2023-06-22 12:33:43] [20101] 28198 28199 28200 28201 28202 28203 28204 28205 28206 28207 28208 28209
## INFO [2023-06-22 12:33:43] [20113] 28210 28211 28212 28213 28214 28215 28216 28217 28218 28219 28220 28221
## INFO [2023-06-22 12:33:43] [20125] 28222 28223 28224 28225 28226 28227 28228 28229 28230 28231 28232 28233
## INFO [2023-06-22 12:33:43] [20137] 28234 28235 28236 28237 28238 28239 28240 28241 28242 28243 28244 28245
## INFO [2023-06-22 12:33:43] [20149] 28246 28247 28248 28249 28250 28251 28252 28253 28254 28255 28256 28257
## INFO [2023-06-22 12:33:43] [20161] 28258 28259 28260 28261 28262 28263 28264 28265 28266 28267 28268 28269
## INFO [2023-06-22 12:33:43] [20173] 28270 28271 28272 28273 28274 28275 28276 28277 28278 28279 28280 28281
## INFO [2023-06-22 12:33:43] [20185] 28282 28283 28284 28285 28286 28287 28288 28289 28290 28291 28292 28293
## INFO [2023-06-22 12:33:43] [20197] 28294 28295 28296 28297 28298 28299 28300 28301 28302 28303 28304 28305
## INFO [2023-06-22 12:33:43] [20209] 28306 28307 28308 28309 28310 28311 28312 28313 28314 28315 28316 28317
## INFO [2023-06-22 12:33:43] [20221] 28318 28319 28320 28321 28322 28323 28324 28325 28326 28327 28328 28329
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## INFO [2023-06-22 12:33:43] [20257] 28354 28355 28356 28357 28358 28359 28360 28361 28362 28363 28364 28365
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## INFO [2023-06-22 12:33:43] [20281] 28378 28379 28380 28381 28382 28383 28384 28385 28386 28387 28388 28389
## INFO [2023-06-22 12:33:43] [20293] 28390 28391 28392 28393 28394 28395 28396 28397 28398 28399 28400 28401
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## INFO [2023-06-22 12:33:43] [20365] 28462 28463 28464 28465 28466 28467 28468 28469 28470 28471 28472 28473
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## INFO [2023-06-22 12:33:43] [20389] 28486 28487 28488 28489 28490 28491 28492 28493 28494 28495 28496 28497
## INFO [2023-06-22 12:33:43] [20401] 28498 28499 28500 28501 28502 28503 28504 28505 28506 28507 28508 28509
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## INFO [2023-06-22 12:33:43] [20497] 28594 28595 28596 28597 28598 28599 28600 28601 28602 28603 28604 28605
## INFO [2023-06-22 12:33:43] [20509] 28606 28607 28608 28609 28610 28611 28612 28613 28614 28615 28616 28617
## INFO [2023-06-22 12:33:43] [20521] 28618 28619 28620 28621 28622 28623 28624 28625 28626 28627 28628 28629
## INFO [2023-06-22 12:33:43] [20533] 28630 28631 28632 28633 28634 28635 28636 28637 28638 28639 28640 28641
## INFO [2023-06-22 12:33:43] [20545] 28642 28643 28644 28645 28646 28647 28648 28649 28650 28651 28652 28653
## INFO [2023-06-22 12:33:43] [20557] 28654 28655 28656 28657 28658 28659 28660 28661 28662 28663 28664 28665
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## INFO [2023-06-22 12:33:43] [20581] 28678 28679 28680 28681 28682 28683 28684 28685 28686 28687 28688 28689
## INFO [2023-06-22 12:33:43] [20593] 28690 28691 28692 28693 28694 28695 28696 28697 28698 28699 28700 28701
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## INFO [2023-06-22 12:33:43] [21193] 29290 29291 29292 29293 29294 29295 29296 29297 29298 29299 29300 29301
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## INFO [2023-06-22 12:33:43] [21673] 29770 29771 29772 29773 29774 29775 29776 29777 29778 29779 29780 29781
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## INFO [2023-06-22 12:33:43] [21901] 29998 29999 30000 30001 30002 30003 30004 30005 30006 30007 30008 30009
## INFO [2023-06-22 12:33:43] [21913] 30010 30011 30012 30013 30014 30015 30016 30017 30018 30019 30020 30021
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## INFO [2023-06-22 12:33:43] [21973] 30070 30071 30072 30073 30074 30075 30076 30077 30078 30079 30080 30081
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## INFO [2023-06-22 12:33:43] [22117] 30214 30215 30216 30217 30218 30219 30220 30221 30222 30223 30224 30225
## INFO [2023-06-22 12:33:43] [22129] 30226 30227 30228 30229 30230 30231 30232 30233 30234 30235 30236 30237
## INFO [2023-06-22 12:33:43] [22141] 30238 30239 30240 30241 30242 30243 30244 30245 30246 30247 30248 30249
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## INFO [2023-06-22 12:33:43] [22189] 30286 30287 30288 30289 30290 30291 30292 30293 30294 30295 30296 30297
## INFO [2023-06-22 12:33:43] [22201] 30298 30299 30300 30301 30302 30303 30304 30305 30306 30307 30308 30309
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## INFO [2023-06-22 12:33:43] [22573] 30670 30671 30672 30673 30674 30675 30676 30677 30678 30679 30680 30681
## INFO [2023-06-22 12:33:43] [22585] 30682 30683 30684 30685 30686 30687 30688 30689 30690 30691 30692 30693
## INFO [2023-06-22 12:33:43] [22597] 30694 30695 30696 30697 30698 30699 30700 30701 30702 30703 30704 30705
## INFO [2023-06-22 12:33:43] [22609] 30706 30707 30708 30709 30710 30711 30712 30713 30714 30715 30716 30717
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## INFO [2023-06-22 12:33:43] [22669] 30766 30767 30768 30769 30770 30771 30772 30773 30774 30775 30776 30777
## INFO [2023-06-22 12:33:43] [22681] 30778 30779 30780 30781 30782 30783 30784 30785 30786 30787 30788 30789
## INFO [2023-06-22 12:33:43] [22693] 30790 30791 30792 30793 30794 30795 30796 30797 30798 30799 30800 30801
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## INFO [2023-06-22 12:33:43] [22897] 30994 30995 30996 30997 30998 30999 31000 31001 31002 31003 31004 31005
## INFO [2023-06-22 12:33:43] [22909] 31006 31007 31008 31009 31010 31011 31012 31013 31014 31015 31016 31017
## INFO [2023-06-22 12:33:43] [22921] 31018 31019 31020 31021 31022 31023 31024 31025 31026 31027 31028 31029
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## INFO [2023-06-22 12:33:43] [23089] 31186 31187 31188 31189 31190 31191 31192 31193 31194 31195 31196 31197
## INFO [2023-06-22 12:33:43] [23101] 31198 31199 31200 31201 31202 31203 31204 31205 31206 31207 31208 31209
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## INFO [2023-06-22 12:33:43] [23137] 31234 31235 31236 31237 31238 31239 31240 31241 31242 31243 31244 31245
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## INFO [2023-06-22 12:33:43] [23833] 31930 31931 31932 31933 31934 31935 31936 31937 31938 31939 31940 31941
## INFO [2023-06-22 12:33:43] [23845] 31942 31943 31944 31945 31946 31947 31948 31949 31950 31951 31952 31953
## INFO [2023-06-22 12:33:43] [23857] 31954 31955 31956 31957 31958 31959 31960 31961 31962 31963 31964 31965
## INFO [2023-06-22 12:33:43] [23869] 31966 31967 31968 31969 31970 31971 31972 31973 31974 31975 31976 31977
## INFO [2023-06-22 12:33:43] [23881] 31978 31979 31980 31981 31982 31983 31984 31985 31986 31987 31988 31989
## INFO [2023-06-22 12:33:43] [23893] 31990 31991 31992 31993 31994 31995 31996 31997 31998 31999 32000 32001
## INFO [2023-06-22 12:33:43] [23905] 32002 32003 32004 32005 32006 32007 32008 32009 32010 32011 32012 32013
## INFO [2023-06-22 12:33:43] [23917] 32014 32015 32016 32017 32018 32019 32020 32021 32022 32023 32024 32025
## INFO [2023-06-22 12:33:43] [23929] 32026 32027 32028 32029 32030 32031 32032 32033 32034 32035 32036 32037
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## INFO [2023-06-22 12:33:43] [23977] 32074 32075 32076 32077 32078 32079 32080 32081 32082 32083 32084 32085
## INFO [2023-06-22 12:33:43] [23989] 32086 32087 32088 32089 32090 32091 32092 32093 32094 32095 32096 32097
## INFO [2023-06-22 12:33:43] [24001] 32098 32099 32100 32101 32102 32103 32104 32105 32106 32107 32108 32109
## INFO [2023-06-22 12:33:43] [24013] 32110 32111 32112 32113 32114 32115 32116 32117 32118 32119 32120 32121
## INFO [2023-06-22 12:33:43] [24025] 32122 32123 32124 32125 32126 32127 32128 32129 32130 32131 32132 32133
## INFO [2023-06-22 12:33:43] [24037] 32134 32135 32136 32137 32138 32139 32140 32141 32142 32143 32144 32145
## INFO [2023-06-22 12:33:43] [24049] 32146 32147 32148 32149 32150 32151 32152 32153 32154 32155 32156 32157
## INFO [2023-06-22 12:33:43] [24061] 32158 32159 32160 32161 32162 32163 32164 32165 32166 32167 32168 32169
## INFO [2023-06-22 12:33:43] [24073] 32170 32171 32172 32173 32174 32175 32176 32177 32178 32179 32180 32181
## INFO [2023-06-22 12:33:43] [24085] 32182 32183 32184 32185 32186 32187 32188 32189 32190 32191 32192 32193
## INFO [2023-06-22 12:33:43] [24097] 32194 32195 32196 32197 32198 32199 32200 32201 32202 32203 32204 32205
## INFO [2023-06-22 12:33:43] [24109] 32206 32207 32208 32209 32210 32211 32212 32213 32214 32215 32216 32217
## INFO [2023-06-22 12:33:43] [24121] 32218 32219 32220 32221 32222 32223 32224 32225 32226 32227 32228 32229
## INFO [2023-06-22 12:33:43] [24133] 32230 32231 32232 32233 32234 32235 32236 32237 32238 32239 32240 32241
## INFO [2023-06-22 12:33:43] [24145] 32242 32243 32244 32245 32246 32247 32248 32249 32250 32251 32252 32253
## INFO [2023-06-22 12:33:43] [24157] 32254 32255 32256 32257 32258 32259 32260 32261 32262 32263 32264 32265
## INFO [2023-06-22 12:33:43] [24169] 32266 32267 32268 32269 32270 32271 32272 32273 32274 32275 32276 32277
## INFO [2023-06-22 12:33:43] [24181] 32278 32279 32280 32281 32282 32283 32284 32285 32286 32287 32288 32289
## INFO [2023-06-22 12:33:43] [24193] 32290 32291 32292 32293 32294 32295 32296 32297 32298 32299 32300 32301
## INFO [2023-06-22 12:33:43] [24205] 32302 32303 32304 32305 32306 32307 32308 32309 32310 32311 32312 32313
## INFO [2023-06-22 12:33:43] [24217] 32314 32315 32316 32317 32318 32319 32320 32321 32322 32323 32324 32325
## INFO [2023-06-22 12:33:43] [24229] 32326 32327 32328 32329 32330 32331 32332 32333 32334 32335 32336 32337
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## INFO [2023-06-22 12:33:43] [24505] 32602 32603 32604 32605 32606 32607 32608 32609 32610 32611 32612 32613
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## INFO [2023-06-22 12:33:43] [24709] 32806 32807 32808 32809 32810 32811 32812 32813 32814 32815 32816 32817
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## INFO [2023-06-22 12:33:43] [24889] 32986 32987 32988 32989 32990 32991 32992 32993 32994 32995 32996 32997
## INFO [2023-06-22 12:33:43] [24901] 32998 32999 33000 33001 33002 33003 33004 33005 33006 33007 33008 33009
## INFO [2023-06-22 12:33:43] [24913] 33010 33011 33012 33013 33014 33015 33016 33017 33018 33019 33020 33021
## INFO [2023-06-22 12:33:43] [24925] 33022 33023 33024 33025 33026 33027 33028 33029 33030 33031 33032 33033
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## INFO [2023-06-22 12:33:43] [24949] 33046 33047 33048 33049 33050 33051 33052 33053 33054 33055 33056 33057
## INFO [2023-06-22 12:33:43] [24961] 33058 33059 33060 33061 33062 33063 33064 33065 33066 33067 33068 33069
## INFO [2023-06-22 12:33:43] [24973] 33070 33071 33072 33073 33074 33075 33076 33077 33078 33079 33080 33081
## INFO [2023-06-22 12:33:43] [24985] 33082 33083 33084 33085 33086 33087 33088 33089 33090 33091 33092 33093
## INFO [2023-06-22 12:33:43] [24997] 33094 33095 33096 33097 33098 33099 33100 33101 33102 33103 33104 33105
## INFO [2023-06-22 12:33:43] [25009] 33106 33107 33108 33109 33110 33111 33112 33113 33114 33115 33116 33117
## INFO [2023-06-22 12:33:43] [25021] 33118 33119 33120 33121 33122 33123 33124 33125 33126 33127 33128 33129
## INFO [2023-06-22 12:33:43] [25033] 33130 33131 33132 33133 33134 33135 33136 33137 33138 33139 33140 33141
## INFO [2023-06-22 12:33:43] [25045] 33142 33143 33144 33145 33146 33147 33148 33149 33150 33151 33152 33153
## INFO [2023-06-22 12:33:43] [25057] 33154 33155 33156 33157 33158 33159 33160 33161 33162 33163 33164 33165
## INFO [2023-06-22 12:33:43] [25069] 33166 33167 33168 33169 33170 33171 33172 33173 33174 33175 33176 33177
## INFO [2023-06-22 12:33:43] [25081] 33178 33179 33180 33181 33182 33183 33184 33185 33186 33187 33188 33189
## INFO [2023-06-22 12:33:43] [25093] 33190 33191 33192 33193 33194 33195 33196 33197 33198 33199 33200 33201
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## INFO [2023-06-22 12:33:43] [29473] 37570 37571 37572 37573 37574 37575 37576 37577 37578 37579 37580 37581
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## INFO [2023-06-22 12:33:43] [29533] 37630 37631 37632 37633 37634 37635 37636 37637 37638 37639 37640 37641
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## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $x$MITF
## INFO [2023-06-22 12:33:43]    [1]  1128  1129  1130  1131  1132  1133  1134  1135  1136  1137  1138  1139
## INFO [2023-06-22 12:33:43]   [13]  1140  1141  1142  1143  1144  1145  1146  1147  1148  1149  1150  1151
## INFO [2023-06-22 12:33:43]   [25]  1152  1153  1154  1155  1156  1157  1158  1159  1160  1161  1162  1163
## INFO [2023-06-22 12:33:43]   [37]  1164  1165  1166  1167  1168  1169  1170  1171  1172  1173  1174  1175
## INFO [2023-06-22 12:33:43]   [49]  1176  1177  1178  1179  1180  1181  1182  1183  1184  1185  1186  1187
## INFO [2023-06-22 12:33:43]   [61]  1188  1189  1190  1191  1192  1193  1194  1195  1196  1197  1198  1199
## INFO [2023-06-22 12:33:43]   [73]  1200  1201  1202  1203  1204  1205  1206  1207  1208  1209  1210  1211
## INFO [2023-06-22 12:33:43]   [85]  1212  1213  1214  1215  1216  1217  1218  1219  1220  1221  1222  1223
## INFO [2023-06-22 12:33:43]   [97]  1224  1225  1226  1227  1228  1229  1230  1231  1232  1233  1234  1235
## INFO [2023-06-22 12:33:43]  [109]  1236  1237  1238  1239  1240  1241  1242  1243  1244  1245  1246  1247
## INFO [2023-06-22 12:33:43]  [121]  1248  1249  1250  1251  1252  1253  1254  1255  1256  1257  1258  1259
## INFO [2023-06-22 12:33:43]  [133]  1260  1261  1262  1263  1264  1265  1266  1267  1268  1269  1270  1271
## INFO [2023-06-22 12:33:43]  [145]  1272  1273  1274  1275  1276  1277  1278  1279  1280  1281  1282  1283
## INFO [2023-06-22 12:33:43]  [157]  1284  1285  1286  1287  1288  1289  1290  1291  1292  1293  1294  1295
## INFO [2023-06-22 12:33:43]  [169]  1296  1297  1298  1299  1300  1301  1302  1303  1304  1305  1306  1307
## INFO [2023-06-22 12:33:43]  [181]  1308  1309  1310  1311  1312  1313  1314  1315  1316  1317  1318  1319
## INFO [2023-06-22 12:33:43]  [193]  1320  1321  1322  1323  1324  1325  1326  1327  1328  1329  1330  1331
## INFO [2023-06-22 12:33:43]  [205]  1332  1333  1334  1335  1336  1337  1338  1339  1340  1341  1342  1343
## INFO [2023-06-22 12:33:43]  [217]  1344  1345  1346  1347  1348  1349  1350  1351  1352  1353  1354  1355
## INFO [2023-06-22 12:33:43]  [229]  1356  1357  1358  1359  1360  1361  1362  1363  1364  1365  1366  1367
## INFO [2023-06-22 12:33:43]  [241]  1368  1369  1370  1371  1372  1373  1374  1375  1376  1377  1378  1379
## INFO [2023-06-22 12:33:43]  [253]  1380  1381  1382  1383  1384  1385  1386  1387  1388  1389  1390  1391
## INFO [2023-06-22 12:33:43]  [265]  1392  1393  1394  1395  1396  1397  1398  1399  1400  1401  1402  1403
## INFO [2023-06-22 12:33:43]  [277]  1404  1405  1406  1407  1408  1409  1410  1411  1412  1413  1414  1415
## INFO [2023-06-22 12:33:43]  [289]  1416  1417  1418  1419  1420  1421  1422  1423  1424  1425  1426  1427
## INFO [2023-06-22 12:33:43]  [301]  1428  1429  1430  1431  1432  1433  1434  1435  1436  1437  1438  1439
## INFO [2023-06-22 12:33:43]  [313]  1440  1441  1442  1443  1444  1445  1446  1447  1448  1449  1450  1451
## INFO [2023-06-22 12:33:43]  [325]  1452  1453  1454  1455  1456  1457  1458  1459  1460  1461  1462  1463
## INFO [2023-06-22 12:33:43]  [337]  1464  1465  1466  1467  1468  1469  1470  1471  1472  1473  1474  1475
## INFO [2023-06-22 12:33:43]  [349]  1476  1477  1478  1479  1480  1481  1482  1483  1484  1485  1486  1487
## INFO [2023-06-22 12:33:43]  [361]  1488  1489  1490  1491  1492  1493  1494  1495  1496  1497  1498  1499
## INFO [2023-06-22 12:33:43]  [373]  1500  1501  1502  1503  1504  1505  1506  1507  1508  1509  1510  1511
## INFO [2023-06-22 12:33:43]  [385]  1512  1513  1514  1515  1516  1517  1518  1519  1520  1521  1522  1523
## INFO [2023-06-22 12:33:43]  [397]  1524  1525  1526  1527  1528  1529  1530  1531  1532  1533  1534  1535
## INFO [2023-06-22 12:33:43]  [409]  1536  1537  1538  1539  1540  1541  1542  1543  1544  1545  1546  1547
## INFO [2023-06-22 12:33:43]  [421]  1548  1549  1550  1551  1552  1553  1554  1555  1556  1557  1558  1559
## INFO [2023-06-22 12:33:43]  [433]  1560  1561  1562  1563  1564  1565  1566  1567  1568  1569  1570  1571
## INFO [2023-06-22 12:33:43]  [445]  1572  1573  1574  1575  1576  1577  1578  1579  1580  1581  1582  1583
## INFO [2023-06-22 12:33:43]  [457]  1584  1585  1586  1587  1588  1589  1590  1591  1592  1593  1594  1595
## INFO [2023-06-22 12:33:43]  [469]  1596  1597  1598  1599  1600  1601  1602  1603  1604  1605  1606  1607
## INFO [2023-06-22 12:33:43]  [481]  1608  1609  1610  1611  1612  1613  1614  1615  1616  1617  1618  1619
## INFO [2023-06-22 12:33:43]  [493]  1620  1621  1622  1623  1624  1625  1626  1627  1628  1629  1630  1631
## INFO [2023-06-22 12:33:43]  [505]  1632  1633  1634  1635  1636  1637  1638  1639  1640  1641  1642  1643
## INFO [2023-06-22 12:33:43]  [517]  1644  1645  1646  1647  1648  1649  1650  1651  1652  1653  1654  1655
## INFO [2023-06-22 12:33:43]  [529]  1656  1657  1658  1659  1660  1661  1662  1663  1664  1665  1666  1667
## INFO [2023-06-22 12:33:43]  [541]  1668  1669  1670  1671  1672  1673  1674  1675  1676  1677  1678  1679
## INFO [2023-06-22 12:33:43]  [553]  1680  1681  1682  1683  1684  1685  1686  1687  1688  1689  1690  1691
## INFO [2023-06-22 12:33:43]  [565]  1692  1693  1694  1695  1696  1697  1698  1699  1700  1701  1702  1703
## INFO [2023-06-22 12:33:43]  [577]  1704  1705  1706  1707  1708  1709  1710  1711  1712  1713  1714  1715
## INFO [2023-06-22 12:33:43]  [589]  1716  1717  1718  1719  1720  1721  1722  1723  1724  1725  1726  1727
## INFO [2023-06-22 12:33:43]  [601]  1728  1729  1730  1731  1732  1733  1734  1735  1736  1737  1738  1739
## INFO [2023-06-22 12:33:43]  [613]  1740  1741  1742  1743  1744  1745  1746  1747  1748  1749  1750  1751
## INFO [2023-06-22 12:33:43]  [625]  1752  1753  1754  1755  1756  1757  1758  1759  1760  1761  1762  1763
## INFO [2023-06-22 12:33:43]  [637]  1764  1765  1766  1767  1768  1769  1770  1771  1772  1773  1774  1775
## INFO [2023-06-22 12:33:43]  [649]  1776  1777  1778  1779  1780  1781  1782  1783  1784  1785  1786  1787
## INFO [2023-06-22 12:33:43]  [661]  1788  1789  1790  1791  1792  1793  1794  1795  1796  1797  1798  1799
## INFO [2023-06-22 12:33:43]  [673]  1800  1801  1802  1803  1804  1805  1806  1807  1808  1809  1810  1811
## INFO [2023-06-22 12:33:43]  [685]  1812  1813  1814  1815  1816  1817  1818  1819  1820  1821  1822  1823
## INFO [2023-06-22 12:33:43]  [697]  1824  1825  1826  1827  1828  1829  1830  1831  1832  1833  1834  1835
## INFO [2023-06-22 12:33:43]  [709]  1836  1837  1838  1839  1840  1841  1842  1843  1844  1845  1846  1847
## INFO [2023-06-22 12:33:43]  [721]  1848  1849  1850  1851  1852  1853  1854  1855  1856  1857  1858  1859
## INFO [2023-06-22 12:33:43]  [733]  1860  1861  1862  1863  1864  1865  1866  1867  1868  1869  1870  1871
## INFO [2023-06-22 12:33:43]  [745]  1872  1873  1874  1875  1876  1877  1878  1879  1880  1881  1882  1883
## INFO [2023-06-22 12:33:43]  [757]  1884  1885  1886  1887  1888  1889  1890  1891  1892  1893  1894  1895
## INFO [2023-06-22 12:33:43]  [769]  1896  1897  1898  1899  1900  1901  1902  1903  1904  1905  1906  1907
## INFO [2023-06-22 12:33:43]  [781]  1908  1909  1910  1911  1912  1913  1914  1915  1916  1917  1918  1919
## INFO [2023-06-22 12:33:43]  [793]  1920  1921  1922  1923  1924  1925  1926  1927  1928  1929  1930  1931
## INFO [2023-06-22 12:33:43]  [805]  1932  1933  1934  1935  1936  1937  1938  1939  1940  1941  1942  1943
## INFO [2023-06-22 12:33:43]  [817]  1944  1945  1946  1947  1948  1949  1950  1951  1952  1953  1954  1955
## INFO [2023-06-22 12:33:43]  [829]  1956  1957  1958  1959  1960  1961  1962  1963  1964  1965  1966  1967
## INFO [2023-06-22 12:33:43]  [841]  1968  1969  1970  1971  1972  1973  1974  1975  1976  1977  1978  1979
## INFO [2023-06-22 12:33:43]  [853]  1980  1981  1982  1983  1984  1985  1986  1987  1988  1989  1990  1991
## INFO [2023-06-22 12:33:43]  [865]  1992  1993  1994  1995  1996  1997  1998  1999  2000  2001  2002  2003
## INFO [2023-06-22 12:33:43]  [877]  2004  2005  2006  2007  2008  2009  2010  2011  2012  2013  2014  2015
## INFO [2023-06-22 12:33:43]  [889]  2016  2017  2018  2019  2020  2021  2022  2023  2024  2025  2026  2027
## INFO [2023-06-22 12:33:43]  [901]  2028  2029  2030  2031  2032  2033  2034  2035  2036  2037  2038  2039
## INFO [2023-06-22 12:33:43]  [913]  2040  2041  2042  2043  2044  2045  2046  2047  2048  2049  2050  2051
## INFO [2023-06-22 12:33:43]  [925]  2052  2053  2054  2055  2056  2057  2058  2059  2060  2061  2062  2063
## INFO [2023-06-22 12:33:43]  [937]  2064  2065  2066  2067  2068  2069  2070  2071  2072  2073  2074  2075
## INFO [2023-06-22 12:33:43]  [949]  2076  2077  2078  2079  2080  2081  2082  2083  2084  2085  2086  2087
## INFO [2023-06-22 12:33:43]  [961]  2088  2089  2090  2091  2092  2093  2094  2095  2096  2097  2098  2099
## INFO [2023-06-22 12:33:43]  [973]  2100  2101  2102  2103  2104  2105  2106  2107  2108  2109  2110  2111
## INFO [2023-06-22 12:33:43]  [985]  2112  2113  2114  2115  2116  2117  2118  2119  2120  2121  2122  2123
## INFO [2023-06-22 12:33:43]  [997]  2124  2125  2126  2127  2128  2129  2130  2131  2132  2133  2134  2135
## INFO [2023-06-22 12:33:43] [1009]  2136  2137  2138  2139  2140  2141  2142  2143  2144  2145  2146  2147
## INFO [2023-06-22 12:33:43] [1021]  2148  2149  2150  2151  2152  2153  2154  2155  2156  2157  2158  2159
## INFO [2023-06-22 12:33:43] [1033]  2160  2161  2162  2163  2164  2165  2166  2167  2168  2169  2170  2171
## INFO [2023-06-22 12:33:43] [1045]  2172  2173  2174  2175  2176  2177  2178  2179  2180  2181  2182  2183
## INFO [2023-06-22 12:33:43] [1057]  2184  2185  2186  2187  2188  2189  2190  2191  2192  2193  2194  2195
## INFO [2023-06-22 12:33:43] [1069]  2196  2197  2198  2199  2200  2201  2202  2203  2204  2205  2206  2207
## INFO [2023-06-22 12:33:43] [1081]  2208  2209  2210  2211  2212  2213  2214  2215  2216  2217  2218  2219
## INFO [2023-06-22 12:33:43] [1093]  2220  2221  2222  2223  2224  2225  2226  2227  2228  2229  2230  2231
## INFO [2023-06-22 12:33:43] [1105]  2232  2233  2234  2235  2236  2237  2238  2239  2240  2241  2242  2243
## INFO [2023-06-22 12:33:43] [1117]  2244  2245  2246  2247  2248  2249  2250  2251  2252  2253  2254  2255
## INFO [2023-06-22 12:33:43] [1129]  2256  2257  2258  2259  2260  2261  2262  2263  2264  2265  2266  2267
## INFO [2023-06-22 12:33:43] [1141]  2268  2269  2270  2271  2272  2273  2274  2275  2276  2277  2278  2279
## INFO [2023-06-22 12:33:43] [1153]  2280  2281  2282  2283  2284  2285  2286  2287  2288  2289  2290  2291
## INFO [2023-06-22 12:33:43] [1165]  2292  2293  2294  2295  2296  2297  2298  2299  2300  2301  2302  2303
## INFO [2023-06-22 12:33:43] [1177]  2304  2305  2306  2307  2308  2309  2310  2311  2312  2313  2314  2315
## INFO [2023-06-22 12:33:43] [1189]  2316  2317  2318  2319  2320  2321  2322  2323  2324  2325  2326  2327
## INFO [2023-06-22 12:33:43] [1201]  2328  2329  2330  2331  2332  2333  2334  2335  2336  2337  2338  2339
## INFO [2023-06-22 12:33:43] [1213]  2340  2341  2342  2343  2344  2345  2346  2347  2348  2349  2350  2351
## INFO [2023-06-22 12:33:43] [1225]  2352  2353  2354  2355  2356  2357  2358  2359  2360  2361  2362  2363
## INFO [2023-06-22 12:33:43] [1237]  2364  2365  2366  2367  2368  2369  2370  2371  2372  2373  2374  2375
## INFO [2023-06-22 12:33:43] [1249]  2376  2377  2378  2379  2380  2381  2382  2383  2384  2385  2386  2387
## INFO [2023-06-22 12:33:43] [1261]  2388  2389  2390  2391  2392  2393  2394  2395  2396  2397  2398  2399
## INFO [2023-06-22 12:33:43] [1273]  2400  2401  2402  2403  2404  2405  2406  2407  2408  2409  2410  2411
## INFO [2023-06-22 12:33:43] [1285]  2412  2413  2414  2415  2416  2417  2418  2419  2420  2421  2422  2423
## INFO [2023-06-22 12:33:43] [1297]  2424  2425  2426  2427  2428  2429  2430  2431  2432  2433  2434  2435
## INFO [2023-06-22 12:33:43] [1309]  2436  2437  2438  2439  2440  2441  2442  2443  2444  2445  2446  2447
## INFO [2023-06-22 12:33:43] [1321]  2448  2449  2450  2451  2452  2453  2454  2455  2456  2457  2458  2459
## INFO [2023-06-22 12:33:43] [1333]  2460  2461  2462  2463  2464  2465  2466  2467  2468  2469  2470  2471
## INFO [2023-06-22 12:33:43] [1345]  2472  2473  2474  2475  2476  2477  2478  2479  2480  2481  2482  2483
## INFO [2023-06-22 12:33:43] [1357]  2484  2485  2486  2487  2488  2489  2490  2491  2492  2493  2494  2495
## INFO [2023-06-22 12:33:43] [1369]  2496  2497  2498  2499  2500  2501  2502  2503  2504  2505  2506  2507
## INFO [2023-06-22 12:33:43] [1381]  2508  2509  2510  2511  2512  2513  2514  2515  2516  2517  2518  2519
## INFO [2023-06-22 12:33:43] [1393]  2520  2521  2522  2523  2524  2525  2526  2527  2528  2529  2530  2531
## INFO [2023-06-22 12:33:43] [1405]  2532  2533  2534  2535  2536  2537  2538  2539  2540  2541  2542  2543
## INFO [2023-06-22 12:33:43] [1417]  2544  2545  2546  2547  2548  2549  2550  2551  2552  2553  2554  2555
## INFO [2023-06-22 12:33:43] [1429]  2556  2557  2558  2559  2560  2561  2562  2563  2564  2565  2566  2567
## INFO [2023-06-22 12:33:43] [1441]  2568  2569  2570  2571  2572  2573  2574  2575  2576  2577  2578  2579
## INFO [2023-06-22 12:33:43] [1453]  2580  2581  2582  2583  2584  2585  2586  2587  2588  2589  2590  2591
## INFO [2023-06-22 12:33:43] [1465]  2592  2593  2594  2595  2596  2597  2598  2599  2600  2601  2602  2603
## INFO [2023-06-22 12:33:43] [1477]  2604  2605  2606  2607  2608  2609  2610  2611  2612  2613  2614  2615
## INFO [2023-06-22 12:33:43] [1489]  2616  2617  2618  2619  2620  2621  2622  2623  2624  2625  2626  2627
## INFO [2023-06-22 12:33:43] [1501]  2628  2629  2630  2631  2632  2633  2634  2635  2636  2637  2638  2639
## INFO [2023-06-22 12:33:43] [1513]  2640  2641  2642  2643  2644  2645  2646  2647  2648  2649  2650  2651
## INFO [2023-06-22 12:33:43] [1525]  2652  2653  2654  2655  2656  2657  2658  2659  2660  2661  2662  2663
## INFO [2023-06-22 12:33:43] [1537]  2664  2665  2666  2667  2668  2669  2670  2671  2672  2673  2674  2675
## INFO [2023-06-22 12:33:43] [1549]  2676  2677  2678  2679  2680  2681  2682  2683  2684  2685  2686  2687
## INFO [2023-06-22 12:33:43] [1561]  2688  2689  2690  2691  2692  2693  2694  2695  2696  2697  2698  2699
## INFO [2023-06-22 12:33:43] [1573]  2700  2701  2702  2703  2704  2705  2706  2707  2708  2709  2710  2711
## INFO [2023-06-22 12:33:43] [1585]  2712  2713  2714  2715  2716  2717  2718  2719  2720  2721  2722  2723
## INFO [2023-06-22 12:33:43] [1597]  2724  2725  2726  2727  2728  2729  2730  2731  2732  2733  2734  2735
## INFO [2023-06-22 12:33:43] [1609]  2736  2737  2738  2739  2740  2741  2742  2743  2744  2745  2746  2747
## INFO [2023-06-22 12:33:43] [1621]  2748  2749  2750  2751  2752  2753  2754  2755  2756  2757  2758  2759
## INFO [2023-06-22 12:33:43] [1633]  2760  2761  2762  2763  2764  2765  2766  2767  2768  2769  2770  2771
## INFO [2023-06-22 12:33:43] [1645]  2772  2773  2774  2775  2776  2777  2778  2779  2780  2781  2782  2783
## INFO [2023-06-22 12:33:43] [1657]  2784  2785  2786  2787  2788  2789  2790  2791  2792  2793  2794  2795
## INFO [2023-06-22 12:33:43] [1669]  2796  2797  2798  2799  2800  2801  2802  2803  2804  2805  2806  2807
## INFO [2023-06-22 12:33:43] [1681]  2808  2809  2810  2811  2812  2813  2814  2815  2816  2817  2818  2819
## INFO [2023-06-22 12:33:43] [1693]  2820  2821  2822  2823  2824  2825  2826  2827  2828  2829  2830  2831
## INFO [2023-06-22 12:33:43] [1705]  2832  2833  2834  2835  2836  2837  2838  2839  2840  2841  2842  2843
## INFO [2023-06-22 12:33:43] [1717]  2844  2845  2846  2847  2848  2849  2850  2851  2852  2853  2854  2855
## INFO [2023-06-22 12:33:43] [1729]  2856  2857  2858  2859  2860  2861  2862  2863  2864  2865  2866  2867
## INFO [2023-06-22 12:33:43] [1741]  2868  2869  2870  2871  2872  2873  2874  2875  2876  2877  2878  2879
## INFO [2023-06-22 12:33:43] [1753]  2880  2881  2882  2883  2884  2885  2886  2887  2888  2889  2890  2891
## INFO [2023-06-22 12:33:43] [1765]  2892  2893  2894  2895  2896  2897  2898  2899  2900  2901  2902  2903
## INFO [2023-06-22 12:33:43] [1777]  2904  2905  2906  2907  2908  2909  2910  2911  2912  2913  2914  2915
## INFO [2023-06-22 12:33:43] [1789]  2916  2917  2918  2919  2920  2921  2922  2923  2924  2925  2926  2927
## INFO [2023-06-22 12:33:43] [1801]  2928  2929  2930  2931  2932  2933  2934  2935  2936  2937  2938  2939
## INFO [2023-06-22 12:33:43] [1813]  2940  2941  2942  2943  2944  2945  2946  2947  2948  2949  2950  2951
## INFO [2023-06-22 12:33:43] [1825]  2952  2953  2954  2955  2956  2957  2958  2959  2960  2961  2962  2963
## INFO [2023-06-22 12:33:43] [1837]  2964  2965  2966  2967  2968  2969  2970  2971  2972  2973  2974  2975
## INFO [2023-06-22 12:33:43] [1849]  2976  2977  2978  2979  2980  2981  2982  2983  2984  2985  2986  2987
## INFO [2023-06-22 12:33:43] [1861]  2988  2989  2990  2991  2992  2993  2994  2995  2996  2997  2998  2999
## INFO [2023-06-22 12:33:43] [1873]  3000  3001  3002  3003  3004  3005  3006  3007  3008  3009  3010  3011
## INFO [2023-06-22 12:33:43] [1885]  3012  3013  3014  3015  3016  3017  3018  3019  3020  3021  3022  3023
## INFO [2023-06-22 12:33:43] [1897]  3024  3025  3026  3027  3028  3029  3030  3031  3032  3033  3034  3035
## INFO [2023-06-22 12:33:43] [1909]  3036  3037  3038  3039  3040  3041  3042  3043  3044  3045  3046  3047
## INFO [2023-06-22 12:33:43] [1921]  3048  3049  3050  3051  3052  3053  3054  3055  3056  3057  3058  3059
## INFO [2023-06-22 12:33:43] [1933]  3060  3061  3062  3063  3064  3065  3066  3067  3068  3069  3070  3071
## INFO [2023-06-22 12:33:43] [1945]  3072  3073  3074  3075  3076  3077  3078  3079  3080  3081  3082  3083
## INFO [2023-06-22 12:33:43] [1957]  3084  3085  3086  3087  3088  3089  3090  3091  3092  3093  3094  3095
## INFO [2023-06-22 12:33:43] [1969]  3096  3097  3098  3099  3100  3101  3102  3103  3104  3105  3106  3107
## INFO [2023-06-22 12:33:43] [1981]  3108  3109  3110  3111  3112  3113  3114  3115  3116  3117  3118  3119
## INFO [2023-06-22 12:33:43] [1993]  3120  3121  3122  3123  3124  3125  3126  3127  3128  3129  3130  3131
## INFO [2023-06-22 12:33:43] [2005]  3132  3133  3134  3135  3136  3137  3138  3139  3140  3141  3142  3143
## INFO [2023-06-22 12:33:43] [2017]  3144  3145  3146  3147  3148  3149  3150  3151  3152  3153  3154  3155
## INFO [2023-06-22 12:33:43] [2029]  3156  3157  3158  3159  3160  3161  3162  3163  3164  3165  3166  3167
## INFO [2023-06-22 12:33:43] [2041]  3168  3169  3170  3171  3172  3173  3174  3175  3176  3177  3178  3179
## INFO [2023-06-22 12:33:43] [2053]  3180  3181  3182  3183  3184  3185  3186  3187  3188  3189  3190  3191
## INFO [2023-06-22 12:33:43] [2065]  3192  3193  3194  3195  3196  3197  3198  3199  3200  3201  3202  3203
## INFO [2023-06-22 12:33:43] [2077]  3204  3205  3206  3207  3208  3209  3210  3211  3212  3213  3214  3215
## INFO [2023-06-22 12:33:43] [2089]  3216  3217  3218  3219  3220  3221  3222  3223  3224  3225  3226  3227
## INFO [2023-06-22 12:33:43] [2101]  3228  3229  3230  3231  3232  3233  3234  3235  3236  3237  3238  3239
## INFO [2023-06-22 12:33:43] [2113]  3240  3241  3242  3243  3244  3245  3246  3247  3248  3249  3250  3251
## INFO [2023-06-22 12:33:43] [2125]  3252  3253  3254  3255  3256  3257  3258  3259  3260  3261  3262  3263
## INFO [2023-06-22 12:33:43] [2137]  3264  3265  3266  3267  3268  3269  3270  3271  3272  3273  3274  3275
## INFO [2023-06-22 12:33:43] [2149]  3276  3277  3278  3279  3280  3281  3282  3283  3284  3285  3286  3287
## INFO [2023-06-22 12:33:43] [2161]  3288  3289  3290  3291  3292  3293  3294  3295  3296  3297  3298  3299
## INFO [2023-06-22 12:33:43] [2173]  3300  3301  3302  3303  3304  3305  3306  3307  3308  3309  3310  3311
## INFO [2023-06-22 12:33:43] [2185]  3312  3313  3314  3315  3316  3317  3318  3319  3320  3321  3322  3323
## INFO [2023-06-22 12:33:43] [2197]  3324  3325  3326  3327  3328  3329  3330  3331  3332  3333  3334  3335
## INFO [2023-06-22 12:33:43] [2209]  3336  3337  3338  3339  3340  3341  3342  3343  3344  3345  3346  3347
## INFO [2023-06-22 12:33:43] [2221]  3348  3349  3350  3351  3352  3353  3354  3355  3356  3357  3358  3359
## INFO [2023-06-22 12:33:43] [2233]  3360  3361  3362  3363  3364  3365  3366  3367  3368  3369  3370  3371
## INFO [2023-06-22 12:33:43] [2245]  3372  3373  3374  3375  3376  3377  3378  3379  3380  3381  3382  3383
## INFO [2023-06-22 12:33:43] [2257]  3384  3385  3386  3387  3388  3389  3390  3391  3392  3393  3394  3395
## INFO [2023-06-22 12:33:43] [2269]  3396  3397  3398  3399  3400  3401  3402  3403  3404  3405  3406  3407
## INFO [2023-06-22 12:33:43] [2281]  3408  3409  3410  3411  3412  3413  3414  3415  3416  3417  3418  3419
## INFO [2023-06-22 12:33:43] [2293]  3420  3421  3422  3423  3424  3425  3426  3427  3428  3429  3430  3431
## INFO [2023-06-22 12:33:43] [2305]  3432  3433  3434  3435  3436  3437  3438  3439  3440  3441  3442  3443
## INFO [2023-06-22 12:33:43] [2317]  3444  3445  3446  3447  3448  3449  3450  3451  3452  3453  3454  3455
## INFO [2023-06-22 12:33:43] [2329]  3456  3457  3458  3459  3460  3461  3462  3463  3464  3465  3466  3467
## INFO [2023-06-22 12:33:43] [2341]  3468  3469  3470  3471  3472  3473  3474  3475  3476  3477  3478  3479
## INFO [2023-06-22 12:33:43] [2353]  3480  3481  3482  3483  3484  3485  3486  3487  3488  3489  3490  3491
## INFO [2023-06-22 12:33:43] [2365]  3492  3493  3494  3495  3496  3497  3498  3499  3500  3501  3502  3503
## INFO [2023-06-22 12:33:43] [2377]  3504  3505  3506  3507  3508  3509  3510  3511  3512  3513  3514  3515
## INFO [2023-06-22 12:33:43] [2389]  3516  3517  3518  3519  3520  3521  3522  3523  3524  3525  3526  3527
## INFO [2023-06-22 12:33:43] [2401]  3528  3529  3530  3531  3532  3533  3534  3535  3536  3537  3538  3539
## INFO [2023-06-22 12:33:43] [2413]  3540  3541  3542  3543  3544  3545  3546  3547  3548  3549  3550  3551
## INFO [2023-06-22 12:33:43] [2425]  3552  3553  3554  3555  3556  3557  3558  3559  3560  3561  3562  3563
## INFO [2023-06-22 12:33:43] [2437]  3564  3565  3566  3567  3568  3569  3570  3571  3572  3573  3574  3575
## INFO [2023-06-22 12:33:43] [2449]  3576  3577  3578  3579  3580  3581  3582  3583  3584  3585  3586  3587
## INFO [2023-06-22 12:33:43] [2461]  3588  3589  3590  3591  3592  3593  3594  3595  3596  3597  3598  3599
## INFO [2023-06-22 12:33:43] [2473]  3600  3601  3602  3603  3604  3605  3606  3607  3608  3609  3610  3611
## INFO [2023-06-22 12:33:43] [2485]  3612  3613  3614  3615  3616  3617  3618  3619  3620  3621  3622  3623
## INFO [2023-06-22 12:33:43] [2497]  3624  3625  3626  3627  3628  3629  3630  3631  3632  3633  3634  3635
## INFO [2023-06-22 12:33:43] [2509]  3636  3637  3638  3639  3640  3641  3642  3643  3644  3645  3646  3647
## INFO [2023-06-22 12:33:43] [2521]  3648  3649  3650  3651  3652  3653  3654  3655  3656  3657  3658  3659
## INFO [2023-06-22 12:33:43] [2533]  3660  3661  3662  3663  3664  3665  3666  3667  3668  3669  3670  3671
## INFO [2023-06-22 12:33:43] [2545]  3672  3673  3674  3675  3676  3677  3678  3679  3680  3681  3682  3683
## INFO [2023-06-22 12:33:43] [2557]  3684  3685  3686  3687  3688  3689  3690  3691  3692  3693  3694  3695
## INFO [2023-06-22 12:33:43] [2569]  3696  3697  3698  3699  3700  3701  3702  3703  3704  3705  3706  3707
## INFO [2023-06-22 12:33:43] [2581]  3708  3709  3710  3711  3712  3713  3714  3715  3716  3717  3718  3719
## INFO [2023-06-22 12:33:43] [2593]  3720  3721  3722  3723  3724  3725  3726  3727  3728  3729  3730  3731
## INFO [2023-06-22 12:33:43] [2605]  3732  3733  3734  3735  3736  3737  3738  3739  3740  3741  3742  3743
## INFO [2023-06-22 12:33:43] [2617]  3744  3745  3746  3747  3748  3749  3750  3751  3752  3753  3754  3755
## INFO [2023-06-22 12:33:43] [2629]  3756  3757  3758  3759  3760  3761  3762  3763  3764  3765  3766  3767
## INFO [2023-06-22 12:33:43] [2641]  3768  3769  3770  3771  3772  3773  3774  3775  3776  3777  3778  3779
## INFO [2023-06-22 12:33:43] [2653]  3780  3781  3782  3783  3784  3785  3786  3787  3788  3789  3790  3791
## INFO [2023-06-22 12:33:43] [2665]  3792  3793  3794  3795  3796  3797  3798  3799  3800  3801  3802  3803
## INFO [2023-06-22 12:33:43] [2677]  3804  3805  3806  3807  3808  3809  3810  3811  3812  3813  3814  3815
## INFO [2023-06-22 12:33:43] [2689]  3816  3817  3818  3819  3820  3821  3822  3823  3824  3825  3826  3827
## INFO [2023-06-22 12:33:43] [2701]  3828  3829  3830  3831  3832  3833  3834  3835  3836  3837  3838  3839
## INFO [2023-06-22 12:33:43] [2713]  3840  3841  3842  3843  3844  3845  3846  3847  3848  3849  3850  3851
## INFO [2023-06-22 12:33:43] [2725]  3852  3853  3854  3855  3856  3857  3858  3859  3860  3861  3862  3863
## INFO [2023-06-22 12:33:43] [2737]  3864  3865  3866  3867  3868  3869  3870  3871  3872  3873  3874  3875
## INFO [2023-06-22 12:33:43] [2749]  3876  3877  3878  3879  3880  3881  3882  3883  3884  3885  3886  3887
## INFO [2023-06-22 12:33:43] [2761]  3888  3889  3890  3891  3892  3893  3894  3895  3896  3897  3898  3899
## INFO [2023-06-22 12:33:43] [2773]  3900  3901  3902  3903  3904  3905  3906  3907  3908  3909  3910  3911
## INFO [2023-06-22 12:33:43] [2785]  3912  3913  3914  3915  3916  3917  3918  3919  3920  3921  3922  3923
## INFO [2023-06-22 12:33:43] [2797]  3924  3925  3926  3927  3928  3929  3930  3931  3932  3933  3934  3935
## INFO [2023-06-22 12:33:43] [2809]  3936  3937  3938  3939  3940  3941  3942  3943  3944  3945  3946  3947
## INFO [2023-06-22 12:33:43] [2821]  3948  3949  3950  3951  3952  3953  3954  3955  3956  3957  3958  3959
## INFO [2023-06-22 12:33:43] [2833]  3960  3961  3962  3963  3964  3965  3966  3967  3968  3969  3970  3971
## INFO [2023-06-22 12:33:43] [2845]  3972  3973  3974  3975  3976  3977  3978  3979  3980  3981  3982  3983
## INFO [2023-06-22 12:33:43] [2857]  3984  3985  3986  3987  3988  3989  3990  3991  3992  3993  3994  3995
## INFO [2023-06-22 12:33:43] [2869]  3996  3997  3998  3999  4000  4001  4002  4003  4004  4005  4006  4007
## INFO [2023-06-22 12:33:43] [2881]  4008  4009  4010  4011  4012  4013  4014  4015  4016  4017  4018  4019
## INFO [2023-06-22 12:33:43] [2893]  4020  4021  4022  4023  4024  4025  4026  4027  4028  4029  4030  4031
## INFO [2023-06-22 12:33:43] [2905]  4032  4033  4034  4035  4036  4037  4038  4039  4040  4041  4042  4043
## INFO [2023-06-22 12:33:43] [2917]  4044  4045  4046  4047  4048  4049  4050  4051  4052  4053  4054  4055
## INFO [2023-06-22 12:33:43] [2929]  4056  4057  4058  4059  4060  4061  4062  4063  4064  4065  4066  4067
## INFO [2023-06-22 12:33:43] [2941]  4068  4069  4070  4071  4072  4073  4074  4075  4076  4077  4078  4079
## INFO [2023-06-22 12:33:43] [2953]  4080  4081  4082  4083  4084  4085  4086  4087  4088  4089  4090  4091
## INFO [2023-06-22 12:33:43] [2965]  4092  4093  4094  4095  4096  4097  4098  4099  4100  4101  4102  4103
## INFO [2023-06-22 12:33:43] [2977]  4104  4105  4106  4107  4108  4109  4110  4111  4112  4113  4114  4115
## INFO [2023-06-22 12:33:43] [2989]  4116  4117  4118  4119  4120  4121  4122  4123  4124  4125  4126  4127
## INFO [2023-06-22 12:33:43] [3001]  4128  4129  4130  4131  4132  4133  4134  4135  4136  4137  4138  4139
## INFO [2023-06-22 12:33:43] [3013]  4140  4141  4142  4143  4144  4145  4146  4147  4148  4149  4150  4151
## INFO [2023-06-22 12:33:43] [3025]  4152  4153  4154  4155  4156  4157  4158  4159  4160  4161  4162  4163
## INFO [2023-06-22 12:33:43] [3037]  4164  4165  4166  4167  4168  4169  4170  4171  4172  4173  4174  4175
## INFO [2023-06-22 12:33:43] [3049]  4176  4177  4178  4179  4180  4181  4182  4183  4184  4185  4186  4187
## INFO [2023-06-22 12:33:43] [3061]  4188  4189  4190  4191  4192  4193  4194  4195  4196  4197  4198  4199
## INFO [2023-06-22 12:33:43] [3073]  4200  4201  4202  4203  4204  4205  4206  4207  4208  4209  4210  4211
## INFO [2023-06-22 12:33:43] [3085]  4212  4213  4214  4215  4216  4217  4218  4219  4220  4221  4222  4223
## INFO [2023-06-22 12:33:43] [3097]  4224  4225  4226  4227  4228  4229  4230  4231  4232  4233  4234  4235
## INFO [2023-06-22 12:33:43] [3109]  4236  4237  4238  4239  4240  4241  4242  4243  4244  4245  4246  4247
## INFO [2023-06-22 12:33:43] [3121]  4248  4249  4250  4251  4252  4253  4254  4255  4256  4257  4258  4259
## INFO [2023-06-22 12:33:43] [3133]  4260  4261  4262  4263  4264  4265  4266  4267  4268  4269  4270  4271
## INFO [2023-06-22 12:33:43] [3145]  4272  4273  4274  4275  4276  4277  4278  4279  4280  4281  4282  4283
## INFO [2023-06-22 12:33:43] [3157]  4284  4285  4286  4287  4288  4289  4290  4291  4292  4293  4294  4295
## INFO [2023-06-22 12:33:43] [3169]  4296  4297  4298  4299  4300  4301  4302  4303  4304  4305  4306  4307
## INFO [2023-06-22 12:33:43] [3181]  4308  4309  4310  4311  4312  4313  4314  4315  4316  4317  4318  4319
## INFO [2023-06-22 12:33:43] [3193]  4320  4321  4322  4323  4324  4325  4326  4327  4328  4329  4330  4331
## INFO [2023-06-22 12:33:43] [3205]  4332  4333  4334  4335  4336  4337  4338  4339  4340  4341  4342  4343
## INFO [2023-06-22 12:33:43] [3217]  4344  4345  4346  4347  4348  4349  4350  4351  4352  4353  4354  4355
## INFO [2023-06-22 12:33:43] [3229]  4356  4357  4358  4359  4360  4361  4362  4363  4364  4365  4366  4367
## INFO [2023-06-22 12:33:43] [3241]  4368  4369  4370  4371  4372  4373  4374  4375  4376  4377  4378  4379
## INFO [2023-06-22 12:33:43] [3253]  4380  4381  4382  4383  4384  4385  4386  4387  4388  4389  4390  4391
## INFO [2023-06-22 12:33:43] [3265]  4392  4393  4394  4395  4396  4397  4398  4399  4400  4401  4402  4403
## INFO [2023-06-22 12:33:43] [3277]  4404  4405  4406  4407  4408  4409  4410  4411  4412  4413  4414  4415
## INFO [2023-06-22 12:33:43] [3289]  4416  4417  4418  4419  4420  4421  4422  4423  4424  4425  4426  4427
## INFO [2023-06-22 12:33:43] [3301]  4428  4429  4430  4431  4432  4433  4434  4435  4436  4437  4438  4439
## INFO [2023-06-22 12:33:43] [3313]  4440  4441  4442  4443  4444  4445  4446  4447  4448  4449  4450  4451
## INFO [2023-06-22 12:33:43] [3325]  4452  4453  4454  4455  4456  4457  4458  4459  4460  4461  4462  4463
## INFO [2023-06-22 12:33:43] [3337]  4464  4465  4466  4467  4468  4469  4470  4471  4472  4473  4474  4475
## INFO [2023-06-22 12:33:43] [3349]  4476  4477  4478  4479  4480  4481  4482  4483  4484  4485  4486  4487
## INFO [2023-06-22 12:33:43] [3361]  4488  4489  4490  4491  4492  4493  4494  4495  4496  4497  4498  4499
## INFO [2023-06-22 12:33:43] [3373]  4500  4501  4502  4503  4504  4505  4506  4507  4508  4509  4510  4511
## INFO [2023-06-22 12:33:43] [3385]  4512  4513  4514  4515  4516  4517  4518  4519  4520  4521  4522  4523
## INFO [2023-06-22 12:33:43] [3397]  4524  4525  4526  4527  4528  4529  4530  4531  4532  4533  4534  4535
## INFO [2023-06-22 12:33:43] [3409]  4536  4537  4538  4539  4540  4541  4542  4543  4544  4545  4546  4547
## INFO [2023-06-22 12:33:43] [3421]  4548  4549  4550  4551  4552  4553  4554  4555  4556  4557  4558  4559
## INFO [2023-06-22 12:33:43] [3433]  4560  4561  4562  4563  4564  4565  4566  4567  4568  4569  4570  4571
## INFO [2023-06-22 12:33:43] [3445]  4572  4573  4574  4575  4576  4577  4578  4579  4580  4581  4582  4583
## INFO [2023-06-22 12:33:43] [3457]  4584  4585  4586  4587  4588  4589  4590  4591  4592  4593  4594  4595
## INFO [2023-06-22 12:33:43] [3469]  4596  4597  4598  4599  4600  4601  4602  4603  4604  4605  4606  4607
## INFO [2023-06-22 12:33:43] [3481]  4608  4609  4610  4611  4612  4613  4614  4615  4616  4617  4618  4619
## INFO [2023-06-22 12:33:43] [3493]  4620  4621  4622  4623  4624  4625  4626  4627  4628  4629  4630  4631
## INFO [2023-06-22 12:33:43] [3505]  4632  4633  4634  4635  4636  4637  4638  4639  4640  4641  4642  4643
## INFO [2023-06-22 12:33:43] [3517]  4644  4645  4646  4647  4648  4649  4650  4651  4652  4653  4654  4655
## INFO [2023-06-22 12:33:43] [3529]  4656  4657  4658  4659  4660  4661  4662  4663  4664  4665  4666  4667
## INFO [2023-06-22 12:33:43] [3541]  4668  4669  4670  4671  4672  4673  4674  4675  4676  4677  4678  4679
## INFO [2023-06-22 12:33:43] [3553]  4680  4681  4682  4683  4684  4685  4686  4687  4688  4689  4690  4691
## INFO [2023-06-22 12:33:43] [3565]  4692  4693  4694  4695  4696  4697  4698  4699  4700  4701  4702  4703
## INFO [2023-06-22 12:33:43] [3577]  4704  4705  4706  4707  4708  4709  4710  4711  4712  4713  4714  4715
## INFO [2023-06-22 12:33:43] [3589]  4716  4717  4718  4719  4720  4721  4722  4723  4724  4725  4726  4727
## INFO [2023-06-22 12:33:43] [3601]  4728  4729  4730  4731  4732  4733  4734  4735  4736  4737  4738  4739
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## INFO [2023-06-22 12:33:43] [3625]  4752  4753  4754  4755  4756  4757  4758  4759  4760  4761  4762  4763
## INFO [2023-06-22 12:33:43] [3637]  4764  4765  4766  4767  4768  4769  4770  4771  4772  4773  4774  4775
## INFO [2023-06-22 12:33:43] [3649]  4776  4777  4778  4779  4780  4781  4782  4783  4784  4785  4786  4787
## INFO [2023-06-22 12:33:43] [3661]  4788  4789  4790  4791  4792  4793  4794  4795  4796  4797  4798  4799
## INFO [2023-06-22 12:33:43] [3673]  4800  4801  4802  4803  4804  4805  4806  4807  4808  4809  4810  4811
## INFO [2023-06-22 12:33:43] [3685]  4812  4813  4814  4815  4816  4817  4818  4819  4820  4821  4822  4823
## INFO [2023-06-22 12:33:43] [3697]  4824  4825  4826  4827  4828  4829  4830  4831  4832  4833  4834  4835
## INFO [2023-06-22 12:33:43] [3709]  4836  4837  4838  4839  4840  4841  4842  4843  4844  4845  4846  4847
## INFO [2023-06-22 12:33:43] [3721]  4848  4849  4850  4851  4852  4853  4854  4855  4856  4857  4858  4859
## INFO [2023-06-22 12:33:43] [3733]  4860  4861  4862  4863  4864  4865  4866  4867  4868  4869  4870  4871
## INFO [2023-06-22 12:33:43] [3745]  4872  4873  4874  4875  4876  4877  4878  4879  4880  4881  4882  4883
## INFO [2023-06-22 12:33:43] [3757]  4884  4885  4886  4887  4888  4889  4890  4891  4892  4893  4894  4895
## INFO [2023-06-22 12:33:43] [3769]  4896  4897  4898  4899  4900  4901  4902  4903  4904  4905  4906  4907
## INFO [2023-06-22 12:33:43] [3781]  4908  4909  4910  4911  4912  4913  4914  4915  4916  4917  4918  4919
## INFO [2023-06-22 12:33:43] [3793]  4920  4921  4922  4923  4924  4925  4926  4927  4928  4929  4930  4931
## INFO [2023-06-22 12:33:43] [3805]  4932  4933  4934  4935  4936  4937  4938  4939  4940  4941  4942  4943
## INFO [2023-06-22 12:33:43] [3817]  4944  4945  4946  4947  4948  4949  4950  4951  4952  4953  4954  4955
## INFO [2023-06-22 12:33:43] [3829]  4956  4957  4958  4959  4960  4961  4962  4963  4964  4965  4966  4967
## INFO [2023-06-22 12:33:43] [3841]  4968  4969  4970  4971  4972  4973  4974  4975  4976  4977  4978  4979
## INFO [2023-06-22 12:33:43] [3853]  4980  4981  4982  4983  4984  4985  4986  4987  4988  4989  4990  4991
## INFO [2023-06-22 12:33:43] [3865]  4992  4993  4994  4995  4996  4997  4998  4999  5000  5001  5002  5003
## INFO [2023-06-22 12:33:43] [3877]  5004  5005  5006  5007  5008  5009  5010  5011  5012  5013  5014  5015
## INFO [2023-06-22 12:33:43] [3889]  5016  5017  5018  5019  5020  5021  5022  5023  5024  5025  5026  5027
## INFO [2023-06-22 12:33:43] [3901]  5028  5029  5030  5031  5032  5033  5034  5035  5036  5037  5038  5039
## INFO [2023-06-22 12:33:43] [3913]  5040  5041  5042  5043  5044  5045  5046  5047  5048  5049  5050  5051
## INFO [2023-06-22 12:33:43] [3925]  5052  5053  5054  5055  5056  5057  5058  5059  5060  5061  5062  5063
## INFO [2023-06-22 12:33:43] [3937]  5064  5065  5066  5067  5068  5069  5070  5071  5072  5073  5074  5075
## INFO [2023-06-22 12:33:43] [3949]  5076  5077  5078  5079  5080  5081  5082  5083  5084  5085  5086  5087
## INFO [2023-06-22 12:33:43] [3961]  5088  5089  5090  5091  5092  5093  5094  5095  5096  5097  5098  5099
## INFO [2023-06-22 12:33:43] [3973]  5100  5101  5102  5103  5104  5105  5106  5107  5108  5109  5110  5111
## INFO [2023-06-22 12:33:43] [3985]  5112  5113  5114  5115  5116  5117  5118  5119  5120  5121  5122  5123
## INFO [2023-06-22 12:33:43] [3997]  5124  5125  5126  5127  5128  5129  5130  5131  5132  5133  5134  5135
## INFO [2023-06-22 12:33:43] [4009]  5136  5137  5138  5139  5140  5141  5142  5143  5144  5145  5146  5147
## INFO [2023-06-22 12:33:43] [4021]  5148  5149  5150  5151  5152  5153  5154  5155  5156  5157  5158  5159
## INFO [2023-06-22 12:33:43] [4033]  5160  5161  5162  5163  5164  5165  5166  5167  5168  5169  5170  5171
## INFO [2023-06-22 12:33:43] [4045]  5172  5173  5174  5175  5176  5177  5178  5179  5180  5181  5182  5183
## INFO [2023-06-22 12:33:43] [4057]  5184  5185  5186  5187  5188  5189  5190  5191  5192  5193  5194  5195
## INFO [2023-06-22 12:33:43] [4069]  5196  5197  5198  5199  5200  5201  5202  5203  5204  5205  5206  5207
## INFO [2023-06-22 12:33:43] [4081]  5208  5209  5210  5211  5212  5213  5214  5215  5216  5217  5218  5219
## INFO [2023-06-22 12:33:43] [4093]  5220  5221  5222  5223  5224  5225  5226  5227  5228  5229  5230  5231
## INFO [2023-06-22 12:33:43] [4105]  5232  5233  5234  5235  5236  5237  5238  5239  5240  5241  5242  5243
## INFO [2023-06-22 12:33:43] [4117]  5244  5245  5246  5247  5248  5249  5250  5251  5252  5253  5254  5255
## INFO [2023-06-22 12:33:43] [4129]  5256  5257  5258  5259  5260  5261  5262  5263  5264  5265  5266  5267
## INFO [2023-06-22 12:33:43] [4141]  5268  5269  5270  5271  5272  5273  5274  5275  5276  5277  5278  5279
## INFO [2023-06-22 12:33:43] [4153]  5280  5281  5282  5283  5284  5285  5286  5287  5288  5289  5290  5291
## INFO [2023-06-22 12:33:43] [4165]  5292  5293  5294  5295  5296  5297  5298  5299  5300  5301  5302  5303
## INFO [2023-06-22 12:33:43] [4177]  5304  5305  5306  5307  5308  5309  5310  5311  5312  5313  5314  5315
## INFO [2023-06-22 12:33:43] [4189]  5316  5317  5318  5319  5320  5321  5322  5323  5324  5325  5326  5327
## INFO [2023-06-22 12:33:43] [4201]  5328  5329  5330  5331  5332  5333  5334  5335  5336  5337  5338  5339
## INFO [2023-06-22 12:33:43] [4213]  5340  5341  5342  5343  5344  5345  5346  5347  5348  5349  5350  5351
## INFO [2023-06-22 12:33:43] [4225]  5352  5353  5354  5355  5356  5357  5358  5359  5360  5361  5362  5363
## INFO [2023-06-22 12:33:43] [4237]  5364  5365  5366  5367  5368  5369  5370  5371  5372  5373  5374  5375
## INFO [2023-06-22 12:33:43] [4249]  5376  5377  5378  5379  5380  5381  5382  5383  5384  5385  5386  5387
## INFO [2023-06-22 12:33:43] [4261]  5388  5389  5390  5391  5392  5393  5394  5395  5396  5397  5398  5399
## INFO [2023-06-22 12:33:43] [4273]  5400  5401  5402  5403  5404  5405  5406  5407  5408  5409  5410  5411
## INFO [2023-06-22 12:33:43] [4285]  5412  5413  5414  5415  5416  5417  5418  5419  5420  5421  5422  5423
## INFO [2023-06-22 12:33:43] [4297]  5424  5425  5426  5427  5428  5429  5430  5431  5432  5433  5434  5435
## INFO [2023-06-22 12:33:43] [4309]  5436  5437  5438  5439  5440  5441  5442  5443  5444  5445  5446  5447
## INFO [2023-06-22 12:33:43] [4321]  5448  5449  5450  5451  5452  5453  5454  5455  5456  5457  5458  5459
## INFO [2023-06-22 12:33:43] [4333]  5460  5461  5462  5463  5464  5465  5466  5467  5468  5469  5470  5471
## INFO [2023-06-22 12:33:43] [4345]  5472  5473  5474  5475  5476  5477  5478  5479  5480  5481  5482  5483
## INFO [2023-06-22 12:33:43] [4357]  5484  5485  5486  5487  5488  5489  5490  5491  5492  5493  5494  5495
## INFO [2023-06-22 12:33:43] [4369]  5496  5497  5498  5499  5500  5501  5502  5503  5504  5505  5506  5507
## INFO [2023-06-22 12:33:43] [4381]  5508  5509  5510  5511  5512  5513  5514  5515  5516  5517  5518  5519
## INFO [2023-06-22 12:33:43] [4393]  5520  5521  5522  5523  5524  5525  5526  5527  5528  5529  5530  5531
## INFO [2023-06-22 12:33:43] [4405]  5532  5533  5534  5535  5536  5537  5538  5539  5540  5541  5542  5543
## INFO [2023-06-22 12:33:43] [4417]  5544  5545  5546  5547  5548  5549  5550  5551  5552  5553  5554  5555
## INFO [2023-06-22 12:33:43] [4429]  5556  5557  5558  5559  5560  5561  5562  5563  5564  5565  5566  5567
## INFO [2023-06-22 12:33:43] [4441]  5568  5569  5570  5571  5572  5573  5574  5575  5576  5577  5578  5579
## INFO [2023-06-22 12:33:43] [4453]  5580  5581  5582  5583  5584  5585  5586  5587  5588  5589  5590  5591
## INFO [2023-06-22 12:33:43] [4465]  5592  5593  5594  5595  5596  5597  5598  5599  5600  5601  5602  5603
## INFO [2023-06-22 12:33:43] [4477]  5604  5605  5606  5607  5608  5609  5610  5611  5612  5613  5614  5615
## INFO [2023-06-22 12:33:43] [4489]  5616  5617  5618  5619  5620  5621  5622  5623  5624  5625  5626  5627
## INFO [2023-06-22 12:33:43] [4501]  5628  5629  5630  5631  5632  5633  5634  5635  5636  5637  5638  5639
## INFO [2023-06-22 12:33:43] [4513]  5640  5641  5642  5643  5644  5645  5646  5647  5648  5649  5650  5651
## INFO [2023-06-22 12:33:43] [4525]  5652  5653  5654  5655  5656  5657  5658  5659  5660  5661  5662  5663
## INFO [2023-06-22 12:33:43] [4537]  5664  5665  5666  5667  5668  5669  5670  5671  5672  5673  5674  5675
## INFO [2023-06-22 12:33:43] [4549]  5676  5677  5678  5679  5680  5681  5682  5683  5684  5685  5686  5687
## INFO [2023-06-22 12:33:43] [4561]  5688  5689  5690  5691  5692  5693  5694  5695  5696  5697  5698  5699
## INFO [2023-06-22 12:33:43] [4573]  5700  5701  5702  5703  5704  5705  5706  5707  5708  5709  5710  5711
## INFO [2023-06-22 12:33:43] [4585]  5712  5713  5714  5715  5716  5717  5718  5719  5720  5721  5722  5723
## INFO [2023-06-22 12:33:43] [4597]  5724  5725  5726  5727  5728  5729  5730  5731  5732  5733  5734  5735
## INFO [2023-06-22 12:33:43] [4609]  5736  5737  5738  5739  5740  5741  5742  5743  5744  5745  5746  5747
## INFO [2023-06-22 12:33:43] [4621]  5748  5749  5750  5751  5752  5753  5754  5755  5756  5757  5758  5759
## INFO [2023-06-22 12:33:43] [4633]  5760  5761  5762  5763  5764  5765  5766  5767  5768  5769  5770  5771
## INFO [2023-06-22 12:33:43] [4645]  5772  5773  5774  5775  5776  5777  5778  5779  5780  5781  5782  5783
## INFO [2023-06-22 12:33:43] [4657]  5784  5785  5786  5787  5788  5789  5790  5791  5792  5793  5794  5795
## INFO [2023-06-22 12:33:43] [4669]  5796  5797  5798  5799  5800  5801  5802  5803  5804  5805  5806  5807
## INFO [2023-06-22 12:33:43] [4681]  5808  5809  5810  5811  5812  5813  5814  5815  5816  5817  5818  5819
## INFO [2023-06-22 12:33:43] [4693]  5820  5821  5822  5823  5824  5825  5826  5827  5828  5829  5830  5831
## INFO [2023-06-22 12:33:43] [4705]  5832  5833  5834  5835  5836  5837  5838  5839  5840  5841  5842  5843
## INFO [2023-06-22 12:33:43] [4717]  5844  5845  5846  5847  5848  5849  5850  5851  5852  5853  5854  5855
## INFO [2023-06-22 12:33:43] [4729]  5856  5857  5858  5859  5860  5861  5862  5863  5864  5865  5866  5867
## INFO [2023-06-22 12:33:43] [4741]  5868  5869  5870  5871  5872  5873  5874  5875  5876  5877  5878  5879
## INFO [2023-06-22 12:33:43] [4753]  5880  5881  5882  5883  5884  5885  5886  5887  5888  5889  5890  5891
## INFO [2023-06-22 12:33:43] [4765]  5892  5893  5894  5895  5896  5897  5898  5899  5900  5901  5902  5903
## INFO [2023-06-22 12:33:43] [4777]  5904  5905  5906  5907  5908  5909  5910  5911  5912  5913  5914  5915
## INFO [2023-06-22 12:33:43] [4789]  5916  5917  5918  5919  5920  5921  5922  5923  5924  5925  5926  5927
## INFO [2023-06-22 12:33:43] [4801]  5928  5929  5930  5931  5932  5933  5934  5935  5936  5937  5938  5939
## INFO [2023-06-22 12:33:43] [4813]  5940  5941  5942  5943  5944  5945  5946  5947  5948  5949  5950  5951
## INFO [2023-06-22 12:33:43] [4825]  5952  5953  5954  5955  5956  5957  5958  5959  5960  5961  5962  5963
## INFO [2023-06-22 12:33:43] [4837]  5964  5965  5966  5967  5968  5969  5970  5971  5972  5973  5974  5975
## INFO [2023-06-22 12:33:43] [4849]  5976  5977  5978  5979  5980  5981  5982  5983  5984  5985  5986  5987
## INFO [2023-06-22 12:33:43] [4861]  5988  5989  5990  5991  5992  5993  5994  5995  5996  5997  5998  5999
## INFO [2023-06-22 12:33:43] [4873]  6000  6001  6002  6003  6004  6005  6006  6007  6008  6009  6010  6011
## INFO [2023-06-22 12:33:43] [4885]  6012  6013  6014  6015  6016  6017  6018  6019  6020  6021  6022  6023
## INFO [2023-06-22 12:33:43] [4897]  6024  6025  6026  6027  6028  6029  6030  6031  6032  6033  6034  6035
## INFO [2023-06-22 12:33:43] [4909]  6036  6037  6038  6039  6040  6041  6042  6043  6044  6045  6046  6047
## INFO [2023-06-22 12:33:43] [4921]  6048  6049  6050  6051  6052  6053  6054  6055  6056  6057  6058  6059
## INFO [2023-06-22 12:33:43] [4933]  6060  6061  6062  6063  6064  6065  6066  6067  6068  6069  6070  6071
## INFO [2023-06-22 12:33:43] [4945]  6072  6073  6074  6075  6076  6077  6078  6079  6080  6081  6082  6083
## INFO [2023-06-22 12:33:43] [4957]  6084  6085  6086  6087  6088  6089  6090  6091  6092  6093  6094  6095
## INFO [2023-06-22 12:33:43] [4969]  6096  6097  6098  6099  6100  6101  6102  6103  6104  6105  6106  6107
## INFO [2023-06-22 12:33:43] [4981]  6108  6109  6110  6111  6112  6113  6114  6115  6116  6117  6118  6119
## INFO [2023-06-22 12:33:43] [4993]  6120  6121  6122  6123  6124  6125  6126  6127  6128  6129  6130  6131
## INFO [2023-06-22 12:33:43] [5005]  6132  6133  6134  6135  6136  6137  6138  6139  6140  6141  6142  6143
## INFO [2023-06-22 12:33:43] [5017]  6144  6145  6146  6147  6148  6149  6150  6151  6152  6153  6154  6155
## INFO [2023-06-22 12:33:43] [5029]  6156  6157  6158  6159  6160  6161  6162  6163  6164  6165  6166  6167
## INFO [2023-06-22 12:33:43] [5041]  6168  6169  6170  6171  6172  6173  6174  6175  6176  6177  6178  6179
## INFO [2023-06-22 12:33:43] [5053]  6180  6181  6182  6183  6184  6185  6186  6187  6188  6189  6190  6191
## INFO [2023-06-22 12:33:43] [5065]  6192  6193  6194  6195  6196  6197  6198  6199  6200  6201  6202  6203
## INFO [2023-06-22 12:33:43] [5077]  6204  6205  6206  6207  6208  6209  6210  6211  6212  6213  6214  6215
## INFO [2023-06-22 12:33:43] [5089]  6216  6217  6218  6219  6220  6221  6222  6223  6224  6225  6226  6227
## INFO [2023-06-22 12:33:43] [5101]  6228  6229  6230  6231  6232  6233  6234  6235  6236  6237  6238  6239
## INFO [2023-06-22 12:33:43] [5113]  6240  6241  6242  6243  6244  6245  6246  6247  6248  6249  6250  6251
## INFO [2023-06-22 12:33:43] [5125]  6252  6253  6254  6255  6256  6257  6258  6259  6260  6261  6262  6263
## INFO [2023-06-22 12:33:43] [5137]  6264  6265  6266  6267  6268  6269  6270  6271  6272  6273  6274  6275
## INFO [2023-06-22 12:33:43] [5149]  6276  6277  6278  6279  6280  6281  6282  6283  6284  6285  6286  6287
## INFO [2023-06-22 12:33:43] [5161]  6288  6289  6290  6291  6292  6293  6294  6295  6296  6297  6298  6299
## INFO [2023-06-22 12:33:43] [5173]  6300  6301  6302  6303  6304  6305  6306  6307  6308  6309  6310  6311
## INFO [2023-06-22 12:33:43] [5185]  6312  6313  6314  6315  6316  6317  6318  6319  6320  6321  6322  6323
## INFO [2023-06-22 12:33:43] [5197]  6324  6325  6326  6327  6328  6329  6330  6331  6332  6333  6334  6335
## INFO [2023-06-22 12:33:43] [5209]  6336  6337  6338  6339  6340  6341  6342  6343  6344  6345  6346  6347
## INFO [2023-06-22 12:33:43] [5221]  6348  6349  6350  6351  6352  6353  6354  6355  6356  6357  6358  6359
## INFO [2023-06-22 12:33:43] [5233]  6360  6361  6362  6363  6364  6365  6366  6367  6368  6369  6370  6371
## INFO [2023-06-22 12:33:43] [5245]  6372  6373  6374  6375  6376  6377  6378  6379  6380  6381  6382  6383
## INFO [2023-06-22 12:33:43] [5257]  6384  6385  6386  6387  6388  6389  6390  6391  6392  6393  6394  6395
## INFO [2023-06-22 12:33:43] [5269]  6396  6397  6398  6399  6400  6401  6402  6403  6404  6405  6406  6407
## INFO [2023-06-22 12:33:43] [5281]  6408  6409  6410  6411  6412  6413  6414  6415  6416  6417  6418  6419
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## INFO [2023-06-22 12:33:43] [9205] 37660 37661 37662 37663
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $x$SOX10
## INFO [2023-06-22 12:33:43]    [1]     1     2     3     4     5     6     7     8     9    10    11    12
## INFO [2023-06-22 12:33:43]   [13]    13    14    15    16    17    18    19    20    21    22    23    24
## INFO [2023-06-22 12:33:43]   [25]    25    26    27    28    29    30    31    32    33    34    35    36
## INFO [2023-06-22 12:33:43]   [37]    37    38    39    40    41    42    43    44    45    46    47    48
## INFO [2023-06-22 12:33:43]   [49]    49    50    51    52    53    54    55    56    57    58    59    60
## INFO [2023-06-22 12:33:43]   [61]    61    62    63    64    65    66    67    68    69    70    71    72
## INFO [2023-06-22 12:33:43]   [73]    73    74    75    76    77    78    79    80    81    82    83    84
## INFO [2023-06-22 12:33:43]   [85]    85    86    87    88    89    90    91    92    93    94    95    96
## INFO [2023-06-22 12:33:43]   [97]    97    98    99   100   101   102   103   104   105   106   107   108
## INFO [2023-06-22 12:33:43]  [109]   109   110   111   112   113   114   115   116   117   118   119   120
## INFO [2023-06-22 12:33:43]  [121]   121   122   123   124   125   126   127   128   129   130   131   132
## INFO [2023-06-22 12:33:43]  [133]   133   134   135   136   137   138   139   140   141   142   143   144
## INFO [2023-06-22 12:33:43]  [145]   145   146   147   148   149   150   151   152   153   154   155   156
## INFO [2023-06-22 12:33:43]  [157]   157   158   159   160   161   162   163   164   165   166   167   168
## INFO [2023-06-22 12:33:43]  [169]   169   170   171   172   173   174   175   176   177   178   179   180
## INFO [2023-06-22 12:33:43]  [181]   181   182   183   184   185   186   187   188   189   190   191   192
## INFO [2023-06-22 12:33:43]  [193]   193   194   195   196   197   198   199   200   201   202   203   204
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## INFO [2023-06-22 12:33:43]  [229]   229   230   231   232   233   234   235   236   237   238   239   240
## INFO [2023-06-22 12:33:43]  [241]   241   242   243   244   245   246   247   248   249   250   251   252
## INFO [2023-06-22 12:33:43]  [253]   253   254   255   256   257   258   259   260   261   262   263   264
## INFO [2023-06-22 12:33:43]  [265]   265   266   267   268   269   270   271   272   273   274   275   276
## INFO [2023-06-22 12:33:43]  [277]   277   278   279   280   281   282   283   284   285   286   287   288
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## INFO [2023-06-22 12:33:43]  [349]   349   350   351   352   353   354   355   356   357   358   359   360
## INFO [2023-06-22 12:33:43]  [361]   361   362   363   364   365   366   367   368   369   370   371   372
## INFO [2023-06-22 12:33:43]  [373]   373   374   375   376   377   378   379   380   381   382   383   384
## INFO [2023-06-22 12:33:43]  [385]   385   386   387   388   389   390   391   392   393   394   395   396
## INFO [2023-06-22 12:33:43]  [397]   397   398   399   400   401   402   403   404   405   406   407   408
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## INFO [2023-06-22 12:33:43]  [457]   457   458   459   460   461   462   463   464   465   466   467   468
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## INFO [2023-06-22 12:33:43]  [529]   529   530   531   532   533   534   535   536   537   538   539   540
## INFO [2023-06-22 12:33:43]  [541]   541   542   543   544   545   546   547   548   549   550   551   552
## INFO [2023-06-22 12:33:43]  [553]   553   554   555   556   557   558   559   560   561   562   563   564
## INFO [2023-06-22 12:33:43]  [565]   565   566   567   568   569   570   571   572   573   574   575   576
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## INFO [2023-06-22 12:33:43]  [589]   589   590   591   592   593   594   595   596   597   598   599   600
## INFO [2023-06-22 12:33:43]  [601]   601   602   603   604   605   606   607   608   609   610   611   612
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## INFO [2023-06-22 12:33:43]  [625]   625   626   627   628   629   630   631   632   633   634   635   636
## INFO [2023-06-22 12:33:43]  [637]   637   638   639   640   641   642   643   644   645   646   647   648
## INFO [2023-06-22 12:33:43]  [649]   649   650   651   652   653   654   655   656   657   658   659   660
## INFO [2023-06-22 12:33:43]  [661]   661   662   663   664   665   666   667   668   669   670   671   672
## INFO [2023-06-22 12:33:43]  [673]   673   674   675   676   677   678   679   680   681   682   683   684
## INFO [2023-06-22 12:33:43]  [685]   685   686   687   688   689   690   691   692   693   694   695   696
## INFO [2023-06-22 12:33:43]  [697]   697   698   699   700   701   702   703   704   705   706   707   708
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## INFO [2023-06-22 12:33:43]  [721]   721   722   723   724   725   726   727   728   729   730   731   732
## INFO [2023-06-22 12:33:43]  [733]   733   734   735   736   737   738   739   740   741   742   743   744
## INFO [2023-06-22 12:33:43]  [745]   745   746   747   748   749   750   751   752   753   754   755   756
## INFO [2023-06-22 12:33:43]  [757]   757   758   759   760   761   762   763   764   765   766   767   768
## INFO [2023-06-22 12:33:43]  [769]   769   770   771   772   773   774   775   776   777   778   779   780
## INFO [2023-06-22 12:33:43]  [781]   781   782   783   784   785   786   787   788   789   790   791   792
## INFO [2023-06-22 12:33:43]  [793]   793   794   795   796   797   798   799   800   801   802   803   804
## INFO [2023-06-22 12:33:43]  [805]   805   806   807   808   809   810   811   812   813   814   815   816
## INFO [2023-06-22 12:33:43]  [817]   817   818   819   820   821   822   823   824   825   826   827   828
## INFO [2023-06-22 12:33:43]  [829]   829   830   831   832   833   834   835   836   837   838   839   840
## INFO [2023-06-22 12:33:43]  [841]   841   842   843   844   845   846   847   848   849   850   851   852
## INFO [2023-06-22 12:33:43]  [853]   853   854   855   856   857   858   859   860   861   862   863   864
## INFO [2023-06-22 12:33:43]  [865]   865   866   867   868   869   870   871   872   873   874   875   876
## INFO [2023-06-22 12:33:43]  [877]   877   878   879   880   881   882   883   884   885   886   887   888
## INFO [2023-06-22 12:33:43]  [889]   889   890   891   892   893   894   895   896   897   898   899   900
## INFO [2023-06-22 12:33:43]  [901]   901   902   903   904   905   906   907   908   909   910   911   912
## INFO [2023-06-22 12:33:43]  [913]   913   914   915   916   917   918   919   920   921   922   923   924
## INFO [2023-06-22 12:33:43]  [925]   925   926   927   928   929   930   931   932   933   934   935   936
## INFO [2023-06-22 12:33:43]  [937]   937   938   939   940   941   942   943   944   945   946   947   948
## INFO [2023-06-22 12:33:43]  [949]   949   950   951   952   953   954   955   956   957   958   959   960
## INFO [2023-06-22 12:33:43]  [961]   961   962   963   964   965   966   967   968   969   970   971   972
## INFO [2023-06-22 12:33:43]  [973]   973   974   975   976   977   978   979   980   981   982   983   984
## INFO [2023-06-22 12:33:43]  [985]   985   986   987   988   989   990   991   992   993   994   995   996
## INFO [2023-06-22 12:33:43]  [997]   997   998   999  1000  1001  1002  1003  1004  1005  1006  1007  1008
## INFO [2023-06-22 12:33:43] [1009]  1009  1010  1011  1012  1013  1014  1015  1016  1017  1018  1019  1020
## INFO [2023-06-22 12:33:43] [1021]  1021  1022  1023  1024  1025  1026  1027  1028  1029  1030  1031  1032
## INFO [2023-06-22 12:33:43] [1033]  1033  1034  1035  1036  1037  1038  1039  1040  1041  1042  1043  1044
## INFO [2023-06-22 12:33:43] [1045]  1045  1046  1047  1048  1049  1050  1051  1052  1053  1054  1055  1056
## INFO [2023-06-22 12:33:43] [1057]  1057  1058  1059  1060  1061  1062  1063  1064  1065  1066  1067  1068
## INFO [2023-06-22 12:33:43] [1069]  1069  1070  1071  1072  1073  1074  1075  1076  1077  1078  1079  1080
## INFO [2023-06-22 12:33:43] [1081]  1081  1082  1083  1084  1085  1086  1087  1088  1089  1090  1091  1092
## INFO [2023-06-22 12:33:43] [1093]  1093  1094  1095  1096  1097  1098  1099  1100  1101  1102  1103  1104
## INFO [2023-06-22 12:33:43] [1105]  1105  1106  1107  1108  1109  1110  1111  1112  1113  1114  1115  1116
## INFO [2023-06-22 12:33:43] [1117]  1117  1118  1119  1120  1121  1122  1123  1124  1125  1126  1127  8058
## INFO [2023-06-22 12:33:43] [1129]  8059  8060  8061  8062  8063  8064  8065  8066  8067  8068  8069  8070
## INFO [2023-06-22 12:33:43] [1141]  8071  8072  8073  8074  8075  8076  8077  8078  8079  8080  8081  8082
## INFO [2023-06-22 12:33:43] [1153]  8083  8084  8085  8086  8087  8088  8089  8090  8091  8092  8093  8094
## INFO [2023-06-22 12:33:43] [1165]  8095  8096  8097 32879 32880 32881 32882 32883 32884 32885 32886 32887
## INFO [2023-06-22 12:33:43] [1177] 32888 32889 32890 32891 32892 32893 32894 32895 32896 32897 32898 32899
## INFO [2023-06-22 12:33:43] [1189] 32900 32901 32902 32903 32904 32905 32906 32907 32908 32909 32910 32911
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## INFO [2023-06-22 12:33:43] [1285] 32996 32997 32998 32999 33000 33001 33002 33003 33004 33005 33006 33007
## INFO [2023-06-22 12:33:43] [1297] 33008 33009 33010 33011 33012 33013 33014 33015 33016 33017 33018 33019
## INFO [2023-06-22 12:33:43] [1309] 33020 33021 33022 33023 33024 33025 33026 33027 33028 33029 33030 33031
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## INFO [2023-06-22 12:33:43] [1417] 33128 33129 33130 33131 33132 33133 33134 33135 33136 33137 33138 33139
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## INFO [2023-06-22 12:33:43] [1465] 33176 33177 33178 33179 33180 33181 33182 33183 33184 33185 33186 33187
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## INFO [2023-06-22 12:33:43] [1501] 33212 33213 33214 33215 33216 33217 33218 33219 33220 33221 33222 33223
## INFO [2023-06-22 12:33:43] [1513] 33224 33225 33226 33227 33228 33229 33230 33231 33232 33233 33234 33235
## INFO [2023-06-22 12:33:43] [1525] 33236 33237 33238 33239 33240 33241 33242 33243 33244 33245 33246 33247
## INFO [2023-06-22 12:33:43] [1537] 33248 33249 33250 33251 33252 33253 33254 33255 33256 33257 33258 33259
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## INFO [2023-06-22 12:33:43] [1597] 33308 33309 33310 33311 33312 33313 33314 33315 33316 33317 33318 33319
## INFO [2023-06-22 12:33:43] [1609] 33320 33321 33322 33323 33324 33325 33326 33327 33328 33329 33330 33331
## INFO [2023-06-22 12:33:43] [1621] 33332 33333 33334 33335 33336 33337 33338 33339 33340 33341 33342 33343
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## INFO [2023-06-22 12:33:43] [1645] 33356 33357 33358 33359 33360 33361 33362 33363 33364 33365 33366 33367
## INFO [2023-06-22 12:33:43] [1657] 33368 33369 33370 33371 33372 33373 33374 33375 33376 33377 33378 33379
## INFO [2023-06-22 12:33:43] [1669] 33380 33381 33382 33383 33384 33385 33386 33387 33388 33389 33390 33391
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## INFO [2023-06-22 12:33:43] [1693] 33404 33405 33406 33407 33408 33409 33410 33411 33412 33413 33414 33415
## INFO [2023-06-22 12:33:43] [1705] 33416 33417 33418 33419 33420 33421 33422 33423 33424 33425 33426 33427
## INFO [2023-06-22 12:33:43] [1717] 33428 33429 33430 33431 33432 33433 33434 33435 33436 33437 33438 33439
## INFO [2023-06-22 12:33:43] [1729] 33440 33441 33442 33443 33444 33445 33446 33447 33448 33449 33450 33451
## INFO [2023-06-22 12:33:43] [1741] 33452 33453 33454 33455 33456 33457 33458 33459 33460 33461 33462 33463
## INFO [2023-06-22 12:33:43] [1753] 33464 33465 33466 33467 33468 33469 33470 33471 33472 33473 33474 33475
## INFO [2023-06-22 12:33:43] [1765] 33476 33477 33478 33479 33480 33481 33482 33483 33484 33485 33486 33487
## INFO [2023-06-22 12:33:43] [1777] 33488 33489 33490 33491 33492 33493 33494 33495 33496 33497 33498 33499
## INFO [2023-06-22 12:33:43] [1789] 33500 33501 33502 33503 33504 33505 33506 33507 33508 33509 33510 33511
## INFO [2023-06-22 12:33:43] [1801] 33512 33513 33514 33515 33516 33517 33518 33519 33520 33521 33522 33523
## INFO [2023-06-22 12:33:43] [1813] 33524 33525 33526 33527 33528 33529 33530 33531 33532 33533 33534 33535
## INFO [2023-06-22 12:33:43] [1825] 33536 33537 33538 33539 33540 33541 33542 33543 33544 33545 33546 33547
## INFO [2023-06-22 12:33:43] [1837] 33548 33549 33550 33551 33552 33553 33554 33555 33556 33557 33558 33559
## INFO [2023-06-22 12:33:43] [1849] 33560 33561 33562 33563 33564 33565 33566 33567 33568 33569 33570 33571
## INFO [2023-06-22 12:33:43] [1861] 33572 33573 33574 33575 33576 33577 33578 33579 33580 33581 33582 33583
## INFO [2023-06-22 12:33:43] [1873] 33584 33585 33586 33587 33588 33589 33590 33591 33592 33593 33594 33595
## INFO [2023-06-22 12:33:43] [1885] 33596 33597 33598 33599 33600 33601 33602 33603 33604 33605 33606 33607
## INFO [2023-06-22 12:33:43] [1897] 33608 33609 33610 33611 33612 33613 33614 33615 33616 33617 33618 33619
## INFO [2023-06-22 12:33:43] [1909] 33620 33621 33622 33623 33624 33625 33626 33627 33628 33629 33630 33631
## INFO [2023-06-22 12:33:43] [1921] 33632 33633 33634 33635 33636 33637 33638 33639 33640 33641 33642 33643
## INFO [2023-06-22 12:33:43] [1933] 33644 33645 33646 33647 33648 33649 33650 33651 33652 33653 33654 33655
## INFO [2023-06-22 12:33:43] [1945] 33656 33657 33658 33659 33660 33661 33662 33663 33664 33665 33666 33667
## INFO [2023-06-22 12:33:43] [1957] 33668 33669 33670 33671 33672 33673 33674 33675 33676 33677 33678 33679
## INFO [2023-06-22 12:33:43] [1969] 33680 33681 33682 33683 33684 33685 33686 33687 33688 33689 33690 33691
## INFO [2023-06-22 12:33:43] [1981] 33692 33693 33694 33695 33696 33697 33698 33699 33700 33701 33702 33703
## INFO [2023-06-22 12:33:43] [1993] 33704 33705 33706 33707 33708 33709 33710 33711 33712 33713 33714 33715
## INFO [2023-06-22 12:33:43] [2005] 33716 33717 33718 33719 33720 33721 33722 33723 33724 33725 33726 33727
## INFO [2023-06-22 12:33:43] [2017] 33728 33729 33730 33731 33732 33733 33734 33735 33736 33737 33738 33739
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## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $filename
## INFO [2023-06-22 12:33:43] NULL
## INFO [2023-06-22 12:33:43] 
## INFO [2023-06-22 12:33:43] $disable.logging
## INFO [2023-06-22 12:33:43] [1] TRUE
## INFO [2023-06-22 12:33:43]
## $p.value
##      BRG1 MITF SOX10          pval
## [1,]    0    1     1 7.824528e-215
## [2,]    1    0     1  0.000000e+00
## [3,]    1    1     0  0.000000e+00
## 
## $vennCounts
##      BRG1 MITF SOX10 Counts count.BRG1 count.MITF count.SOX10
## [1,]    0    0     0 411865          0          0           0
## [2,]    0    0     1   1127          0          0        1127
## [3,]    0    1     0   6930          0       6930           0
## [4,]    0    1     1     40          0         40          40
## [5,]    1    0     0  24781      24781          0           0
## [6,]    1    0     1   2547       3491          0        2572
## [7,]    1    1     0   1784       1907       1822           0
## [8,]    1    1     1    454        695        487         475
## attr(,"class")
## [1] "VennCounts"

According to the hypergeometric test p-values all pairwise comparisons are highly significant (=0). This has to be taken very carefully as it depends largely on the background estimation that we may have over-estimated. If you are not sure about your estimation, you will prefer to use a non-parametric approach based on your peak genomic distribution to estimate randomness. To this end the TxDb.Hsapiens.UCSC.hg38.knownGene is used.

3.3.1.1 Is the overlap significant?

ChIPpeakAnno provides the preparePool and peakPermTest functions to compute this test. These tests are made by pair, we will look at SOX10/MITF overlap significance as an example.

# Prepare a pool of random peaks following the characteristics of our peak sets
pool <- preparePool(txdb,peaks$SOX10,bindingType="TSS",featureType="transcript",seqn=paste0("chr",c(1:22,"X","Y")))
# Create the permPool object needed for peakPermTest
pool <- new("permPool",grs=pool$grs[1],N=length(peaks$SOX10))
SOX10.MITF <- peakPermTest(peaks$SOX10, peaks$MITF, pool=pool, seed=1, force.parallel=FALSE)
SOX10.MITF
## $cntOverlaps
## P-value: 0.0099009900990099
## Z-score: 143.9367
## Number of iterations: 100
## Alternative: greater
## Evaluation of the original region set: 437
## Evaluation function: cntOverlaps
## Randomization function: randPeaks
## 
## attr(,"class")
## [1] "permTestResultsList"
plot(SOX10.MITF)

Venn diagrams are widely used to represent overlaps, intersections. However, in ChIP-seq analysis, the definition of the peaks is dependent on the peak caller, the FDR thresholds (what about peaks just bellow the threshold). The overlap is also difficult to assess, indeed do we call an overlap a 1 nucleotide an intersection ? It is one of the numerous parameters that can be tuned …

Are different combinations of TFs bind specific genomic regions ?

coocs <- as(ovl$peaklist,"GRangesList")
# apply annotatePeak to each set of peaks in the list coocs
peakAnnoList <- lapply(coocs, annotatePeak, TxDb=txdb,
                        tssRegion=c(-1000, 100), annoDb="org.Hs.eg.db",
                        verbose=FALSE)
## 'select()' returned 1:many mapping between keys and columns
## 'select()' returned 1:many mapping between keys and columns
## 'select()' returned 1:many mapping between keys and columns
## 'select()' returned 1:many mapping between keys and columns
## 'select()' returned 1:many mapping between keys and columns
## 'select()' returned 1:many mapping between keys and columns
## 'select()' returned 1:many mapping between keys and columns
# Plot peak distribution relatively to gene features
plotAnnoBar(peakAnnoList)

# Plot peak distribution relatively to their distance to the TSS
plotDistToTSS(peakAnnoList)

3.3.2 Heatmaps / Profiles

One way to circumvent hard thresholds and relatively arbitrary choices, we can choose to use heatmap and average profile representations. To this end, we need to define the reference point of view. We use the BRG1 peak centers.

Load bigwig file for MITF and SOX10 at BRG1 peaks.

# Load and add bigwig profiles for MITF and SOX10 in cvglist already containing
# BRG1
names(cvglist)
## [1] "BRG1"
cvglist$MITF <- import(file.path(params$chipseq,params$mitf.bw),format="BigWig",
                      which=extended.5K.BRG1,
                      as="RleList")
cvglist$SOX10 <- import(file.path(params$chipseq,params$sox10.bw),format="BigWig",
                      which=extended.5K.BRG1,
                      as="RleList")
names(cvglist)
## [1] "BRG1"  "MITF"  "SOX10"

Prepare the matrices binned in 50bp windows.

sig <- featureAlignedSignal(cvglist, centers.BRG1,
                           upstream=5000, downstream=5000,n.tile=200)
lapply(sig, dim)
## $BRG1
## [1] 30874   200
## 
## $MITF
## [1] 30874   200
## 
## $SOX10
## [1] 30874   200

Create normalized matrices.

## Create a list of normalizedMatrix that is the input format
## for EnrichedHeatmap
BRG1.mat <- lapply(sig, function(x){
  # x represent each element of the sig list
  mat <- as.normalizedMatrix(as.matrix(x),
                      k_upstream = 100,
                      k_downstream = 100,
                      k_target = 0,
                      extend = c(5000, 5000),
                      #signal_name = names(sig[["MITF"]]),
                      target_name = "Peak center"
                      )
  return(mat)
})

We use the partition we computed in section 2.7.2.2

# Define new colors for each heatmap
col_sox10 <-colorRamp2(c(0,3,4), c("white", "blue","black"))
col_mitf <- colorRamp2(c(0,4,5), c("white", "blue","black"))
col_brg1 <- colorRamp2(c(0,5,6), c("white", "blue","black"))
# create a legend for the cluster labels
lgd <- Legend(at = c("cluster1", "cluster2", "cluster3", "cluster4","cluster5","cluster6","cluster7","cluster8"),
    title = "Clusters",
    type = "lines", legend_gp = gpar(col = 2:9))
# Add a first column containing the cluster assignment
ht_list <- Heatmap(partition, col = structure(2:9, names = paste0("cluster", 1:8)), name = "partition", show_row_names = FALSE, width = unit(3, "mm")) +
EnrichedHeatmap(BRG1.mat$BRG1, name = "BRG1", col=col_brg1,
  top_annotation = HeatmapAnnotation(lines = anno_enriched(gp = gpar(col = 2:9))),
  column_title = "BRG1") +
EnrichedHeatmap(BRG1.mat$MITF, name = "MITF",
  top_annotation = HeatmapAnnotation(lines = anno_enriched(gp = gpar(col = 2:9))),
  column_title = "MITF", row_title_rot = 0, col=col_mitf) +
EnrichedHeatmap(BRG1.mat$SOX10, name = "SOX10",
  top_annotation = HeatmapAnnotation(lines = anno_enriched(gp = gpar(col = 2:9))),
  column_title = "SOX10", row_title_rot = 0, col=col_sox10)
draw(ht_list, split = partition, annotation_legend_list = list(lgd),
    ht_gap = unit(c(2, 8, 8,8), "mm"))

Lets have a look at the TF binding profiles in cluster 5.

# For each matrix, filter peaks from cluster 5
sig.tmp <- lapply(sig,function(x,part){
    mat <- x[part=="cluster5",]
    return(mat)
  },part=partition)

# plot the average profiles
featureAlignedDistribution(sig.tmp, centers.BRG1,
                           upstream=5000, downstream=5000,
                           type="l",n.tile=200)

3.4 Is gene expression influenced by TF binding to their promoters ?

  • We will concentrate on genes having BRG1 binding close to their TSS. To do that we will plot a heatmap centered on TSS.

First retrieve the TSS positions from the TxDB object

# Generate TSS and promoter GRanges, the function promoters allows to retrieve the
# gene ID (entrez)
TSS <- GenomicFeatures::promoters(txdb, upstream=0, downstream=0, columns="gene_id")

Clean the TSS list removing TSS with no gene ID assigned (column gene_id in the metadata) and on scaffolds (seqnames).
The column gene_id is of type characterList, this type is difficult to manipulate. We then decide to transform it to a character vector. We can’t directly unlist the object because, to save memory, not annotated TSS are assigned empty elements which disappear when unlisting.

# For each element of the characterList we check it's length, if it is 0
# we fill the element with NA. We the unlist.
gene_ids <- unlist(lapply(TSS$gene_id,function(x){
  if (length(x)==0){
     NA
  }
  else {
    x
  }
} ))
# Keep TSS on selected chromosomes annotated with a gene ID and remove
# duplicate IDs due to transcript isoforms. Here, the selection of the
# isoform is random.
TSS <- TSS[as.vector(seqnames(TSS))%in%paste0("chr",c(1:22,"X","Y")) & !is.na(gene_ids) & !duplicated(gene_ids)]

# extend TSS both direction
TSS.extended <- resize(TSS, width = width(TSS)+4000, fix = "center")

Load bigwig profiles for TSS extended regions, create matrices and transform in the enrichedHeatmap recognized format.

# load the bw file for all TFs within the promoter
cvglist <- list()
cvglist$BRG1 <- import(file.path(params$chipseq,params$brg1.bw),format="BigWig",
                      which=TSS.extended,
                      as="RleList")
cvglist$MITF <- import(file.path(params$chipseq,params$mitf.bw),format="BigWig",
                      which=TSS.extended,
                      as="RleList")
cvglist$SOX10 <- import(file.path(params$chipseq,params$sox10.bw),format="BigWig",
                      which=TSS.extended,
                      as="RleList")
# Produce the signal matrices
sig <- featureAlignedSignal(cvglist, TSS,n.tile=400,
                           upstream=2000, downstream=2000)
# Transform the signal matrices as normalizedMatrix
TSS.mat <- lapply(sig, function(x){
  # x represent each element of the sig list
  mat <- as.normalizedMatrix(as.matrix(x),
                      k_upstream = 200,
                      k_downstream = 200,
                      k_target = 0,
                      extend = c(2000, 2000),
                      target_name = "TSS"
                      )
  return(mat)
})

We will compute K-means clustering with kmeans function to define the partitions of the TSS based on BRG1 signal.

# Compute a partition using the kmeans function, asking for 5 clusters
set.seed(20210526)
partition.TSS = paste0("cluster", kmeans(TSS.mat$BRG1, centers = 5)$cluster)
# Specify colors for the position enrichment for each matrix
col_sox10 = colorRamp2(c(0,3,4), c("white", "blue","black"))
col_mitf = colorRamp2(c(0,4,5), c("white", "blue","black"))
col_brg1 = colorRamp2(c(0,5,6), c("white", "blue","black"))
lgd = Legend(at = c("cluster1", "cluster2", "cluster3", "cluster4","cluster5"),
    title = "Clusters",
    type = "lines", legend_gp = gpar(col = 2:6))
ht_list = Heatmap(partition.TSS, col = structure(2:7, names = paste0("cluster", 1:5)), name = "partition", show_row_names = FALSE, width = unit(3, "mm")) +
EnrichedHeatmap(TSS.mat$BRG1, name = "BRG1", col=col_brg1,
  top_annotation = HeatmapAnnotation(lines = anno_enriched(gp = gpar(col = 2:6))),
  column_title = "BRG1") +
EnrichedHeatmap(TSS.mat$MITF, name = "MITF",
  top_annotation = HeatmapAnnotation(lines = anno_enriched(gp = gpar(col = 2:6))),
  column_title = "MITF", row_title_rot = 0, col=col_mitf) +
EnrichedHeatmap(TSS.mat$SOX10, name = "SOX10",
  top_annotation = HeatmapAnnotation(lines = anno_enriched(gp = gpar(col = 2:6))),
  column_title = "SOX10", row_title_rot = 0, col=col_sox10)
draw(ht_list, split = partition.TSS, annotation_legend_list = list(lgd),
    ht_gap = unit(c(2, 8, 8,8), "mm"))

Lets have a look at the TF binding profiles in cluster 4.

# For each matrix, filter peaks from cluster 5
sig.tmp <- lapply(sig,function(x,part){
    mat <- x[part=="cluster4",]
    return(mat)
  },part=partition.TSS)

# plot the average profiles
featureAlignedDistribution(sig.tmp, TSS,
                           upstream=2000, downstream=2000,
                           type="l",n.tile=400)
## Warning in featureAlignedDistribution(sig.tmp, TSS, upstream = 2000, downstream
## = 2000, : feature.gr is set to the center of feature.gr

  • Let’s integrate expression data from RNA-seq experiment.

The goal is to visualize the gene expression according to the cluster the TSS belong.

# load RNA-seq normalized expression data
load(params$rnaseq) # RNAseq
head(RNAseq)
##   Ensembl.Gene.ID    WT.norm shBGR1.norm   logCPM      logFC          FDR
## 1 ENSG00000000003  722.38046   119.10483 4.387012  2.5748948 2.233826e-21
## 2 ENSG00000000419 1481.30280  2514.73393 6.689308 -0.6994493 1.391964e-13
## 3 ENSG00000000457  259.21973   314.27718 5.364018 -0.3167911 3.091766e-05
## 4 ENSG00000000460  333.22470   380.48495 5.562143 -0.1954216 2.875151e-03
## 5 ENSG00000000971   13.42921    13.59959 0.341927  0.6570620 2.536438e-02
## 6 ENSG00000001036 1157.52492  1521.75139 5.567526 -0.3587066 3.117933e-06
##   signif
## 1 stable
## 2 stable
## 3 stable
## 4 stable
## 5 stable
## 6 stable

RNA-seq columns: - Ensembl.Gene.ID: Gene idenfier from ensEMBL (ENSG*****) - WT.norm: normalized expression for wild type cell lines - shBGR1.norm: normalized expression for shBRG1 cell lines - logCPM: average log transformed overall expression - logFC: log fol change between the two conditions - FDR: multi-testing corrected p-value from edgeR statistical test - signif (up, down, stable): significance was set as: FDR < 0.01, logCPM > 5, abs(logFC) > 1

Reads from RNA-seq were assigned to genes modeled from ensEMBL and thus are identified with ensEMBL ID. However, the TSS are annotated with ENTREZ IDs, we thus need to map together the identifiers. We use an OrgDB object for the human genome the available information are displayed using columns().

columns(org.Hs.eg.db)
##  [1] "ACCNUM"       "ALIAS"        "ENSEMBL"      "ENSEMBLPROT"  "ENSEMBLTRANS"
##  [6] "ENTREZID"     "ENZYME"       "EVIDENCE"     "EVIDENCEALL"  "GENENAME"    
## [11] "GENETYPE"     "GO"           "GOALL"        "IPI"          "MAP"         
## [16] "OMIM"         "ONTOLOGY"     "ONTOLOGYALL"  "PATH"         "PFAM"        
## [21] "PMID"         "PROSITE"      "REFSEQ"       "SYMBOL"       "UCSCKG"      
## [26] "UNIPROT"

We then use the function mapIds from AnnotationDbi package with the keys ENSEMBL and ENTREZID. You can see that other identifiers are available from this object (e.g: SYMBOL, REFSEQ, UNIPROT etc).

conv <- mapIds(x=org.Hs.eg.db,
              keys=RNAseq$Ensembl.Gene.ID, # what do we want to be mapped
              column="ENTREZID", # which type of ID we want
              keytype="ENSEMBL") # what type of ID we give
## 'select()' returned 1:many mapping between keys and columns
head(conv)
## ENSG00000000003 ENSG00000000419 ENSG00000000457 ENSG00000000460 ENSG00000000971 
##          "7105"          "8813"         "57147"         "55732"          "3075" 
## ENSG00000001036 
##          "2519"
# names of the vector are ENSEMBL IDs and elements are ENTREZ IDs

We use the match function that allows to return match between the IDs in RNAseq and the ensEMBL IDs from the conversion vector

m <- match(RNAseq$Ensembl.Gene.ID,names(conv))
head(m)
## [1] 1 2 3 4 5 6
# m contains NA for element in the first vector not present in the 2nd
# or the index of the element of the 2nd vector corresponding the those
# in the first
# Attribute the matched ENTREZ ID
RNAseq$ENTREZID <- conv[m]
head(RNAseq)
##   Ensembl.Gene.ID    WT.norm shBGR1.norm   logCPM      logFC          FDR
## 1 ENSG00000000003  722.38046   119.10483 4.387012  2.5748948 2.233826e-21
## 2 ENSG00000000419 1481.30280  2514.73393 6.689308 -0.6994493 1.391964e-13
## 3 ENSG00000000457  259.21973   314.27718 5.364018 -0.3167911 3.091766e-05
## 4 ENSG00000000460  333.22470   380.48495 5.562143 -0.1954216 2.875151e-03
## 5 ENSG00000000971   13.42921    13.59959 0.341927  0.6570620 2.536438e-02
## 6 ENSG00000001036 1157.52492  1521.75139 5.567526 -0.3587066 3.117933e-06
##   signif ENTREZID
## 1 stable     7105
## 2 stable     8813
## 3 stable    57147
## 4 stable    55732
## 5 stable     3075
## 6 stable     2519

We can now associate RNA-seq and TSS information using the ENTREZ IDs and the match function.

# We add the partition (clusters) to the TSS object in order to add the
# clusters to the RNA-seq object
TSS$cluster <- partition.TSS
# The common IDs this time are the ENTREZ IDs
m <- match(RNAseq$ENTREZID,unlist(TSS$gene_id))
RNAseq$cluster <- TSS$cluster[m]
head(RNAseq)
##   Ensembl.Gene.ID    WT.norm shBGR1.norm   logCPM      logFC          FDR
## 1 ENSG00000000003  722.38046   119.10483 4.387012  2.5748948 2.233826e-21
## 2 ENSG00000000419 1481.30280  2514.73393 6.689308 -0.6994493 1.391964e-13
## 3 ENSG00000000457  259.21973   314.27718 5.364018 -0.3167911 3.091766e-05
## 4 ENSG00000000460  333.22470   380.48495 5.562143 -0.1954216 2.875151e-03
## 5 ENSG00000000971   13.42921    13.59959 0.341927  0.6570620 2.536438e-02
## 6 ENSG00000001036 1157.52492  1521.75139 5.567526 -0.3587066 3.117933e-06
##   signif ENTREZID  cluster
## 1 stable     7105 cluster2
## 2 stable     8813 cluster2
## 3 stable    57147 cluster3
## 4 stable    55732 cluster4
## 5 stable     3075 cluster4
## 6 stable     2519 cluster2

We first want to compare the expression between this to condition in the different clusters.
We need to melt the RNAseq object keeping only the expression values in the “WT.norm” and the “shBGR1.norm” columns and the cluster assignment. We want to evaluate the differences using boxplots as bellow.

##    cluster variable      value
## 1 cluster2  WT.norm  722.38046
## 2 cluster2  WT.norm 1481.30280
## 3 cluster3  WT.norm  259.21973
## 4 cluster4  WT.norm  333.22470
## 5 cluster4  WT.norm   13.42921
## 6 cluster2  WT.norm 1157.52492

Show code: plot expression distribution in both condition

 
# melt the RNAseq table to get a data.frame with a column indicating
# the experimental condition, a column with the cluster assignment
# and the expression values

expr.melt <- melt(RNAseq[,c("WT.norm","shBGR1.norm","cluster")])
head(expr.melt)

ggplot(expr.melt,aes(x=cluster,y=log2(value+1))) +
  geom_boxplot(aes(color=variable)) +
  theme_bw() + theme(legend.position = "top") +
  scale_color_manual(values=c(WT.norm="black",shBGR1.norm=colours()[613]))

We can see that there are no visible difference between the conditions even if cluster 3, which has the less BRG1 signal, is much less expressed than the others. We can check if the distribution of significantly differentially expressed genes differs among the clusters using barplots.

Show code: plot significantly differentially expressed genes in clusters

 
# Distribution of differentially expressed genes as barplots
ggplot(RNAseq,aes(x=cluster)) +
  geom_bar(aes(fill=signif),position = "fill",color="black") +
  theme_bw() +
  scale_fill_manual(values=c(up="red",down="blue",stable="white"))

3.5 Are there particular biological function associated with the differentially expressed genes having different BRG1 binding patterns ?

To answer this question, we use the R package clusterProfiler to compute hypergeometric enrichment of biological function in each cluster using KEGG annotation database.
clusterProfiler provide the function compareCluster that allows to analyze and compare enrichment in different group of genes. This function recognize ENTREZ identifiers.


Représentation simplifiée graphique du test hypergéometrique

# load the library
library(clusterProfiler)
# Select genes whose gene expression is significantly changing
# between conditions
geneList <- RNAseq[RNAseq$signif!="stable",]
# The function split help at splitting a vector to a list following categories
# in an other vector.
geneList <- split(geneList$ENTREZID,geneList$cluster)
names(geneList)
## [1] "cluster1" "cluster2" "cluster3" "cluster4" "cluster5"
head(geneList$cluster1)
## [1] "64847" "27072" "51606" "51154" "51619" "57455"
compKEGG <- compareCluster(geneCluster   = geneList,
                         fun           = "enrichKEGG",
                         pvalueCutoff  = 0.05,
                         pAdjustMethod = "BH")
dotplot(compKEGG, showCategory = 15, title = "KEGG Pathway Enrichment Analysis")

Let’s focus on cluster 4 and visualize which genes of the the KEGG pathway “Cell cycle” (hsa04110) are both differentially expressed and bound by BRG1 and MITF. We use the pathview package which maps differential gene expression values to KEGG maps and create a PNG file in your current directory that you get with getwd().

# load the library
library(pathview)
# Retrieve gene id from cluster 4
geneList.cl4 <- geneList$cluster4
# use match function to select correspondant logFC from RNA-seq data
m <- match(geneList.cl4,RNAseq$ENTREZID)
logFC.cl4 <- RNAseq$logFC[m]
names(logFC.cl4) <- geneList.cl4
# call the function
pathview(logFC.cl4,pathway.id = "hsa04110",species = "hsa")

Pathview

3.5.1 Are there published data I could use to enrich my analysis ?

  • Data Mining with ChIP seq data deposited in GEO with ChIPSeeker

There are many ChIP seq data sets that have been published and deposited in GEO database. We can compare our own dataset to those deposited in GEO to search for significant overlap data. Significant overlap of ChIP seq data by different binding proteins may be used to infer cooperative regulation and thus can be used to generate hypotheses.

We collect about 17,000 bed files deposited in GEO, user can use getGEOspecies to get a summary based on spieces.

getGEOspecies()
##                                                                 species  Freq
## 1                                       Actinobacillus pleuropneumoniae     1
## 2                   Actinobacillus pleuropneumoniae serovar 3 str. JL03     1
## 3                                                         Aedes aegypti    11
## 4                                                              Anabaena     6
## 5                                                   Anolis carolinensis     7
## 6                                                     Anopheles gambiae     2
## 7                                                        Apis mellifera    17
## 8                                             Apis mellifera scutellata     1
## 9                                                           Arabidopsis    17
## 10                                                   Arabidopsis lyrata     4
## 11                                                 Arabidopsis thaliana  2473
## 12                                                 Atelerix albiventris     2
## 13                                                    Bombus terrestris     8
## 14                                                           Bos taurus   257
## 15                                              Brachypodium distachyon    10
## 16                                            Branchiostoma lanceolatum    93
## 17                                                        Brassica rapa    12
## 18                                               Caenorhabditis elegans   532
## 19                                                   Callithrix jacchus    48
## 20                                                     Candida albicans    34
## 21                                                 Candida dubliniensis    20
## 22                                                          Canis lupus     1
## 23                                               Canis lupus familiaris    35
## 24                                                Capsaspora owczarzaki    21
## 25                                                        Carica papaya     1
## 26                                        Caulobacter crescentus NA1000     8
## 27                                               Caulobacter vibrioides     2
## 28                                            Chlamydomonas reinhardtii    53
## 29                                                 Chlorocebus aethiops    11
## 30                                                  Chlorocebus sabaeus     6
## 31                                                       Ciona savignyi     4
## 32                                                    Citrullus lanatus     3
## 33                                                   Cleome hassleriana     1
## 34                                                        Columba livia     6
## 35                                           Corynebacterium glutamicum     9
## 36                                                    Crassostrea gigas     4
## 37                                              Cryptococcus neoformans    67
## 38                                                         Cucumis melo     9
## 39                                                      Cucumis sativus     3
## 40                                                      Cyprinus carpio    40
## 41                                                          Danio rerio   532
## 42                                                        Daphnia magna    36
## 43                                                        Daphnia pulex    14
## 44                                             Dictyostelium discoideum    77
## 45                                                    Dimocarpus longan     9
## 46                                             Dromaius novaehollandiae    27
## 47                                                   Drosophila busckii     2
## 48                                              Drosophila melanogaster  1483
## 49                              Drosophila melanogaster;\tSindbis virus     3
## 50                                                   Drosophila miranda     2
## 51                                             Drosophila pseudoobscura     7
## 52                                                  Drosophila simulans    12
## 53                                                   Drosophila virilis    28
## 54                                                Drosophila willistoni     1
## 55                                                    Drosophila yakuba     8
## 56                                                       Equus caballus     1
## 57                                                     Escherichia coli   126
## 58                                             Escherichia coli BW25113     4
## 59                                                Escherichia coli K-12     2
## 60                            Escherichia coli str. K-12 substr. MG1655    16
## 61                                                  Eutrema salsugineum    12
## 62                                                       Fragaria vesca     3
## 63                                                   Fusarium oxysporum     4
## 64                                                        Gallus gallus   292
## 65                                               Gasterosteus aculeatus     1
## 66                                         Geobacter sulfurreducens PCA     3
## 67                                                          Glycine max    31
## 68                                                      Gorilla gorilla     8
## 69                                                   Haloferax volcanii     3
## 70                                                    Helianthus annuus     2
## 71                                                Heterocephalus glaber     4
## 72                                                    Histophilus somni     1
## 73                                                         Homo sapiens 51828
## 74                               Homo sapiens;\tHuman betaherpesvirus 6     2
## 75                              Homo sapiens;\tHuman betaherpesvirus 6A    38
## 76                              Homo sapiens;\tHuman gammaherpesvirus 8    12
## 77                                   Homo sapiens;\tHuman herpesvirus 8     6
## 78                       Homo sapiens;\tHuman poliovirus 1 strain Sabin     5
## 79                  Homo sapiens;\tInfluenza A virus (A/hvPR8/34(H1N1))    12
## 80                                          Homo sapiens;\tMus musculus    13
## 81                                         Homo sapiens;\tSindbis virus     8
## 82                                             Human gammaherpesvirus 4     3
## 83                                                 Human herpesvirus 6B     2
## 84                                                  Human herpesvirus 8     6
## 85                                         Human immunodeficiency virus    11
## 86                                                       Hydra vulgaris     6
## 87                                                 Komagataella phaffii    12
## 88                                                  Larimichthys crocea     7
## 89                                                     Leersia perrieri     1
## 90                                               Legionella pneumophila     5
## 91                                               Leishmania amazonensis     4
## 92                                                     Leishmania major    14
## 93                                     Leishmania major strain Friedlin     4
## 94                                                Leishmania tarentolae    15
## 95                                                       Macaca mulatta   136
## 96                                        Macaca mulatta polyomavirus 1     7
## 97                         Macaca mulatta;\tMacacine gammaherpesvirus 4     3
## 98                                                      Malus domestica    21
## 99                                                Marchantia polymorpha     1
## 100                                                 Medicago truncatula     8
## 101                                                   Mesoplasma florum     1
## 102                                                  Microcebus murinus     6
## 103                                       Moloney murine leukemia virus     9
## 104                                               Monodelphis domestica    31
## 105                                          Moraxella catarrhalis O35E     6
## 106                                                                 Mus     2
## 107                                                        Mus musculus 38038
## 108                             Mus musculus musculus x M. m. castaneus     1
## 109                                          Mus musculus x Mus spretus    11
## 110                       Mus musculus;\tHuman herpesvirus 1 strain KOS     2
## 111                                 Mus musculus;\tMurid herpesvirus 68     2
## 112                                            Musa acuminata AAA Group     3
## 113                                  Mycobacterium abscessus ATCC 19977     4
## 114                                               Mycobacterium marinum     1
## 115                                          Mycobacterium tuberculosis     2
## 116                                    Mycobacterium tuberculosis H37Rv     5
## 117                                         Mycolicibacterium smegmatis     2
## 118                                 Mycolicibacterium smegmatis MC2 155     2
## 119                                                     Myotis brandtii    15
## 120                                               Naumovozyma castellii     1
## 121                                              Nematostella vectensis    31
## 122                                                   Neurospora crassa     3
## 123                                                   Nicotiana tabacum     6
## 124                                            Nicrophorus vespilloides     4
## 125                                        Nippostrongylus brasiliensis     9
## 126                                                 Nomascus leucogenys     1
## 127                                               Oreochromis niloticus     1
## 128                                            Ornithorhynchus anatinus     5
## 129                                                   Oryza brachyantha    11
## 130                                                    Oryza glaberrima     1
## 131                                                      Oryza punctata     1
## 132                                                        Oryza sativa   110
## 133                                         Oryza sativa Japonica Group    17
## 134                                                     Oryzias latipes    26
## 135                                                          Ovis aries     2
## 136                                                     Pan troglodytes   106
## 137                                               Pantherophis guttatus     7
## 138                                                        Papio anubis     3
## 139                                                     Patiria miniata     1
## 140                                             Penicillium chrysogenum     1
## 141                                                   Petunia x hybrida    10
## 142                                              Phascolarctos cinereus     2
## 143                                                 Phaseolus coccineus     2
## 144                                               Plasmodium falciparum   220
## 145                                           Plasmodium falciparum 3D7    43
## 146                                                    Plectus sambesii     1
## 147                                                      Pongo pygmaeus     6
## 148                                                  Procambarus fallax     6
## 149                                              Procambarus virginalis    16
## 150                                         Pseudomonas aeruginosa PAO1     7
## 151                                           Pseudomonas putida KT2440     2
## 152                       Pseudomonas savastanoi pv. phaseolicola 1448A     3
## 153                                                  Pseudozyma aphidis    11
## 154                                                  Pyricularia oryzae    18
## 155                                                 Pyrococcus furiosus     4
## 156                                              Pyrus x bretschneideri     4
## 157                                                   Rattus norvegicus   237
## 158                                             Rhodobacter sphaeroides    12
## 159                                          Rhodopseudomonas palustris     6
## 160                                   Rhodopseudomonas palustris CGA009     3
## 161                                            Romanomermis culicivorax     1
## 162                                            Saccharomyces cerevisiae  3740
## 163                                     Saccharomyces cerevisiae BY4741     8
## 164                                      Saccharomyces cerevisiae S288C    18
## 165                  Saccharomyces cerevisiae x Saccharomyces paradoxus    16
## 166                             Saccharomyces cerevisiae;\tHomo sapiens     2
## 167                             Saccharomyces cerevisiae;\tMus musculus    12
## 168                                          Saccharomyces kudriavzevii     1
## 169                                             Saccharomyces paradoxus     8
## 170                                                Saccharomyces uvarum     1
## 171                                                         Salmo salar    32
## 172 Salmonella enterica subsp. enterica serovar Typhimurium str. SL1344     4
## 173                                                Sarcophilus harrisii     3
## 174                                       Schizosaccharomyces japonicus     2
## 175                                           Schizosaccharomyces pombe   460
## 176                                              Schmidtea mediterranea     7
## 177                                                Solanum lycopersicum    76
## 178                                                   Solanum pennellii    18
## 179                                                     Sorghum bicolor     3
## 180                                               Spodoptera frugiperda    16
## 181                                       Streptomyces coelicolor A3(2)     6
## 182                                       Strongylocentrotus purpuratus    36
## 183                                                          Sus scrofa   334
## 184                                                 synthetic construct    42
## 185                                                 Taeniopygia guttata    21
## 186                                             Tetrahymena thermophila    19
## 187                                       Tetrahymena thermophila CU428     6
## 188                                           Thermus thermophilus HB27     4
## 189                                        Torulaspora microellipsoides     6
## 190                                                   Toxoplasma gondii    21
## 191                                                Toxoplasma gondii RH    12
## 192                                                 Tribolium castaneum    14
## 193                                                Trichinella spiralis     1
## 194                                                     Trichuris muris     4
## 195                                                   Triticum aestivum   127
## 196                                                  Trypanosoma brucei    12
## 197                                                    Tupaia chinensis     7
## 198                                                     Vibrio cholerae     8
## 199                                                      Vitis vinifera     2
## 200                                       Xenopus (Silurana) tropicalis    62
## 201                                                      Xenopus laevis    29
## 202                                                  Xenopus tropicalis   133
## 203                                 Xenopus tropicalis x Xenopus laevis     4
## 204                                                            Zea mays   173

User can access the detail information by getGEOInfo, for each genome version.

hg38 <- getGEOInfo(genome="hg38", simplify=TRUE)
head(hg38)
##       series_id        gsm     organism                                 title
## 16488  GSE58207 GSM1403308 Homo sapiens         Lactimidomycin treated HCT116
## 16489  GSE58207 GSM1403308 Homo sapiens         Lactimidomycin treated HCT116
## 16490  GSE58207 GSM1403307 Homo sapiens          Cycloheximide treated HCT116
## 16491  GSE58207 GSM1403307 Homo sapiens          Cycloheximide treated HCT116
## 20345  GSE67978 GSM1660032 Homo sapiens   H3K27ac_Human_Brain_WhiteMatter_HS2
## 20351  GSE67978 GSM1660029 Homo sapiens H3K27ac_Human_Brain_OccipitalPole_HS2
##                                                                                                                                 supplementary_file
## 16488                                   ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM1403nnn/GSM1403308/suppl/GSM1403308_HCT116_LTM_sense.bedGraph.gz
## 16489                              ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM1403nnn/GSM1403308/suppl/GSM1403308_HCT116_LTM_anti-sense.bedGraph.gz
## 16490                              ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM1403nnn/GSM1403307/suppl/GSM1403307_HCT116_CHX_anti-sense.bedGraph.gz
## 16491                                   ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM1403nnn/GSM1403307/suppl/GSM1403307_HCT116_CHX_sense.bedGraph.gz
## 20345   ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM1660nnn/GSM1660032/suppl/GSM1660032_H3K27ac_Human_Brain_WhiteMatter_HS2_hg38_peaks.narrowPeak.gz
## 20351 ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM1660nnn/GSM1660029/suppl/GSM1660029_H3K27ac_Human_Brain_OccipitalPole_HS2_hg38_peaks.narrowPeak.gz
##       genomeVersion pubmed_id
## 16488          hg38      <NA>
## 16489          hg38      <NA>
## 16490          hg38      <NA>
## 16491          hg38      <NA>
## 20345          hg38      <NA>
## 20351          hg38      <NA>

ChIPseeker provides the function downloadGEObedFiles to download all the bed files of a particular genome.

downloadGEObedFiles(genome="hg38", destDir="hg38")

Or a vector of GSM accession number by downloadGSMbedFiles.

gsm <- hg38$gsm[sample(nrow(hg38), 10)]
downloadGSMbedFiles(gsm, destDir="hg38")

After the download of bed files from GEO, we can pass them to enrichPeakOverlap for testing the significant of overlap. Parameter targetPeak can be the folder, e.g. hg19, that containing bed files. enrichPeakOverlap will parse the folder and compare all the bed files. It is possible to test the overlap with bed files that are mapped to different genome or different genome versions: enrichPeakOverlap provides a parameter chainFile that can pass a chain file and liftOver the targetPeak to the genome version consistent with queryPeak. Signifcant overlap can be used to generate hypothesis of cooperative regulation. By mining the data deposited in GEO, we can identify some putative complex or interacted regulators in gene expression regulation or chromosome remodelling for further validation.

  • The (mod)ENCODE project link

  • The UCSC genome browser link

4 Importance of the annotation databases

In previous annotation steps, we have annotated peaks using annotation from UCSC’s knownGene. The database chosen for annotation can have an impact on subsequent results including data integration such as comparison between genes associated to peaks and gene expression using RNA-seq data for instance.

Let’s look at the overlap between genes expressed in RNA-seq data with genes associated to peaks (let’s remind that peaks are associated to closest genes if no other evidences are used).

## Download GTF files
library(GenomicFeatures)

## Import BRG1 peaks annotated with Ensembl and Refseq annotation
load(params$annot)

## Here is how annotation data were downloaded
# txdb.ensembl = makeTxDbFromGFF("data/ChIPseq/Homo_sapiens.GRCh38.103_UCSC_chr.gtf.gz")
# txdb.refseq = makeTxDbFromUCSC(genome="hg38", tablename="refGene")

## Here is how annotation was performed
# annot <- list()
# annot[["ensembl"]] <- annotatePeak(peaks$BRG1, tssRegion=c(-1000, 100), TxDb=txdb.ensembl, annoDb="org.Hs.eg.db")
# annot[["refseq"]] <- annotatePeak(peaks$BRG1, tssRegion=c(-1000, 100), TxDb=txdb.refseq, annoDb="org.Hs.eg.db")

## Add Gene symbols to RNAseq data
conv.symbol <- mapIds(x=org.Hs.eg.db,
              keys=RNAseq$Ensembl.Gene.ID, # what do we want to be mapped
              column=c("SYMBOL"), # which type of ID we want
              keytype="ENSEMBL") # what type of ID we give

m <- match(RNAseq$Ensembl.Gene.ID,names(conv.symbol))

RNAseq$SYMBOL <- conv.symbol[m]

## Now let's create a venn diagram that compares peak annotation with
## refseq or Ensembl
library(ggVennDiagram)
x <- list(RNAseq=RNAseq[RNAseq$signif=="up",]$SYMBOL,
          Ensembl=as.data.frame(annot$ensembl)$SYMBOL,
          Refseq=as.data.frame(annot$refseq)$SYMBOL
)

ggVennDiagram(x) + scale_fill_gradient(low="white",high = "blue")

5 Session info

sessionInfo()
## R version 4.3.0 (2023-04-21)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Ventura 13.4
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib 
## LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## time zone: Europe/Paris
## tzcode source: internal
## 
## attached base packages:
## [1] stats4    grid      stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] ggVennDiagram_1.2.2                     
##  [2] pathview_1.39.0                         
##  [3] clusterProfiler_4.8.1                   
##  [4] UpSetR_1.4.0                            
##  [5] reshape2_1.4.4                          
##  [6] RColorBrewer_1.1-3                      
##  [7] knitr_1.42                              
##  [8] org.Hs.eg.db_3.17.0                     
##  [9] TxDb.Hsapiens.UCSC.hg38.knownGene_3.17.0
## [10] GenomicFeatures_1.52.0                  
## [11] AnnotationDbi_1.62.1                    
## [12] Biobase_2.60.0                          
## [13] rtracklayer_1.60.0                      
## [14] circlize_0.4.15                         
## [15] ChIPseeker_1.36.0                       
## [16] ChIPpeakAnno_3.34.1                     
## [17] ggplot2_3.4.2                           
## [18] EnrichedHeatmap_1.30.0                  
## [19] GenomicRanges_1.52.0                    
## [20] GenomeInfoDb_1.36.0                     
## [21] IRanges_2.34.0                          
## [22] S4Vectors_0.38.1                        
## [23] BiocGenerics_0.46.0                     
## [24] ComplexHeatmap_2.16.0                   
## 
## loaded via a namespace (and not attached):
##   [1] splines_4.3.0                          
##   [2] BiocIO_1.10.0                          
##   [3] bitops_1.0-7                           
##   [4] ggplotify_0.1.0                        
##   [5] filelock_1.0.2                         
##   [6] tibble_3.2.1                           
##   [7] polyclip_1.10-4                        
##   [8] graph_1.78.0                           
##   [9] XML_3.99-0.14                          
##  [10] lifecycle_1.0.3                        
##  [11] sf_1.0-12                              
##  [12] doParallel_1.0.17                      
##  [13] lattice_0.21-8                         
##  [14] MASS_7.3-60                            
##  [15] magrittr_2.0.3                         
##  [16] sass_0.4.6                             
##  [17] rmarkdown_2.21.3                       
##  [18] plotrix_3.8-2                          
##  [19] jquerylib_0.1.4                        
##  [20] yaml_2.3.7                             
##  [21] cowplot_1.1.1                          
##  [22] DBI_1.1.3                              
##  [23] zlibbioc_1.46.0                        
##  [24] purrr_1.0.1                            
##  [25] ggraph_2.1.0                           
##  [26] RCurl_1.98-1.12                        
##  [27] yulab.utils_0.0.6                      
##  [28] tweenr_2.0.2                           
##  [29] rappdirs_0.3.3                         
##  [30] GenomeInfoDbData_1.2.10                
##  [31] enrichplot_1.20.0                      
##  [32] ggrepel_0.9.3                          
##  [33] tidytree_0.4.2                         
##  [34] units_0.8-2                            
##  [35] codetools_0.2-19                       
##  [36] DelayedArray_0.26.1                    
##  [37] DOSE_3.26.1                            
##  [38] xml2_1.3.4                             
##  [39] ggforce_0.4.1                          
##  [40] tidyselect_1.2.0                       
##  [41] shape_1.4.6                            
##  [42] futile.logger_1.4.3                    
##  [43] aplot_0.1.10                           
##  [44] farver_2.1.1                           
##  [45] viridis_0.6.3                          
##  [46] matrixStats_0.63.0                     
##  [47] BiocFileCache_2.8.0                    
##  [48] rmdformats_1.0.4                       
##  [49] GenomicAlignments_1.36.0               
##  [50] jsonlite_1.8.4                         
##  [51] GetoptLong_1.0.5                       
##  [52] multtest_2.56.0                        
##  [53] e1071_1.7-13                           
##  [54] tidygraph_1.2.3                        
##  [55] survival_3.5-5                         
##  [56] iterators_1.0.14                       
##  [57] foreach_1.5.2                          
##  [58] tools_4.3.0                            
##  [59] progress_1.2.2                         
##  [60] treeio_1.24.0                          
##  [61] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
##  [62] Rcpp_1.0.10                            
##  [63] glue_1.6.2                             
##  [64] gridExtra_2.3                          
##  [65] xfun_0.39                              
##  [66] qvalue_2.32.0                          
##  [67] MatrixGenerics_1.12.0                  
##  [68] dplyr_1.1.2                            
##  [69] withr_2.5.0                            
##  [70] formatR_1.14                           
##  [71] fastmap_1.1.1                          
##  [72] boot_1.3-28.1                          
##  [73] fansi_1.0.4                            
##  [74] caTools_1.18.2                         
##  [75] digest_0.6.31                          
##  [76] R6_2.5.1                               
##  [77] gridGraphics_0.5-1                     
##  [78] colorspace_2.1-0                       
##  [79] GO.db_3.17.0                           
##  [80] gtools_3.9.4                           
##  [81] biomaRt_2.56.0                         
##  [82] RSQLite_2.3.1                          
##  [83] utf8_1.2.3                             
##  [84] tidyr_1.3.0                            
##  [85] generics_0.1.3                         
##  [86] data.table_1.14.8                      
##  [87] class_7.3-22                           
##  [88] prettyunits_1.1.1                      
##  [89] graphlayouts_1.0.0                     
##  [90] InteractionSet_1.28.0                  
##  [91] httr_1.4.5                             
##  [92] S4Arrays_1.0.1                         
##  [93] scatterpie_0.1.9                       
##  [94] regioneR_1.32.0                        
##  [95] pkgconfig_2.0.3                        
##  [96] gtable_0.3.3                           
##  [97] blob_1.2.4                             
##  [98] XVector_0.40.0                         
##  [99] shadowtext_0.1.2                       
## [100] htmltools_0.5.5                        
## [101] bookdown_0.33                          
## [102] fgsea_1.26.0                           
## [103] RBGL_1.76.0                            
## [104] clue_0.3-64                            
## [105] ggupset_0.3.0                          
## [106] scales_1.2.1                           
## [107] png_0.1-8                              
## [108] ggfun_0.0.9                            
## [109] lambda.r_1.2.4                         
## [110] rstudioapi_0.14                        
## [111] rjson_0.2.21                           
## [112] nlme_3.1-162                           
## [113] curl_5.0.0                             
## [114] proxy_0.4-27                           
## [115] cachem_1.0.8                           
## [116] GlobalOptions_0.1.2                    
## [117] stringr_1.5.0                          
## [118] RVenn_1.1.0                            
## [119] KernSmooth_2.23-21                     
## [120] parallel_4.3.0                         
## [121] HDO.db_0.99.1                          
## [122] restfulr_0.0.15                        
## [123] pillar_1.9.0                           
## [124] vctrs_0.6.2                            
## [125] gplots_3.1.3                           
## [126] dbplyr_2.3.2                           
## [127] cluster_2.1.4                          
## [128] Rgraphviz_2.43.0                       
## [129] KEGGgraph_1.59.3                       
## [130] evaluate_0.20                          
## [131] VennDiagram_1.7.3                      
## [132] cli_3.6.1                              
## [133] locfit_1.5-9.7                         
## [134] compiler_4.3.0                         
## [135] futile.options_1.0.1                   
## [136] Rsamtools_2.16.0                       
## [137] rlang_1.1.1                            
## [138] crayon_1.5.2                           
## [139] labeling_0.4.2                         
## [140] classInt_0.4-9                         
## [141] plyr_1.8.8                             
## [142] stringi_1.7.12                         
## [143] viridisLite_0.4.2                      
## [144] BiocParallel_1.34.0                    
## [145] munsell_0.5.0                          
## [146] Biostrings_2.68.0                      
## [147] lazyeval_0.2.2                         
## [148] GOSemSim_2.26.0                        
## [149] Matrix_1.5-4                           
## [150] BSgenome_1.68.0                        
## [151] hms_1.1.3                              
## [152] patchwork_1.1.2                        
## [153] bit64_4.0.5                            
## [154] KEGGREST_1.40.0                        
## [155] highr_0.10                             
## [156] SummarizedExperiment_1.30.1            
## [157] igraph_1.4.2                           
## [158] memoise_2.0.1                          
## [159] bslib_0.4.2                            
## [160] ggtree_3.8.0                           
## [161] fastmatch_1.1-3                        
## [162] bit_4.0.5                              
## [163] downloader_0.4                         
## [164] gson_0.1.0                             
## [165] ape_5.7-1

References

“(2014) Mod/Mouse/humanENCODE: Blacklisted Genomic Regions for Functional Genomics Analysis - Anshul Kundaje.” n.d. Accessed August 26, 2016. https://sites.google.com/site/anshulkundaje/projects/blacklists.
Anders, Simon, Paul Theodor Pyl, and Wolfgang Huber. 2015. “HTSeq—a Python Framework to Work with High-Throughput Sequencing Data.” Bioinformatics 31 (2): 166–69. https://doi.org/10.1093/bioinformatics/btu638.
Anders, and Huber. 2010. “Differential Expression Analysis for Sequence Count Data.” Genome Biology 11.
Dobin, Alexander, Carrie A. Davis, Felix Schlesinger, Jorg Drenkow, Chris Zaleski, Sonali Jha, Philippe Batut, Mark Chaisson, and Thomas R. Gingeras. 2013. “STAR: Ultrafast Universal RNA-Seq Aligner.” Bioinformatics 29 (1): 15–21. https://doi.org/10.1093/bioinformatics/bts635.
Heinz, Sven, Christopher Benner, Nathanael Spann, Eric Bertolino, Yin C. Lin, Peter Laslo, Jason X. Cheng, Cornelis Murre, Harinder Singh, and Christopher K. Glass. 2010. “Simple Combinations of Lineage-Determining Transcription Factors Prime Cis-Regulatory Elements Required for Macrophage and b Cell Identities.” Molecular Cell 38 (4): 576–89. https://doi.org/10.1016/j.molcel.2010.05.004.
Langmead, Ben, Cole Trapnell, Mihai Pop, and Steven L. Salzberg. 2009. “Ultrafast and Memory-Efficient Alignment of Short DNA Sequences to the Human Genome.” Genome Biology 10 (3): R25. https://doi.org/10.1186/gb-2009-10-3-r25.
Laurette, Patrick, Thomas Strub, Dana Koludrovic, Céline Keime, Stéphanie Le Gras, Hannah Seberg, Eric Van Otterloo, et al. 2015. “Transcription Factor MITF and Remodeller BRG1 Define Chromatin Organisation at Regulatory Elements in Melanoma Cells.” Edited by Michael R Green. eLife 4 (March): e06857. https://doi.org/10.7554/eLife.06857.
Martin, Marcel. 2011. “Cutadapt Removes Adapter Sequences from High-Throughput Sequencing Reads.” EMBnet.journal 17 (1): pp. 10–12. http://journal.embnet.org/index.php/embnetjournal/article/view/200.
Quinlan, Aaron R., and Ira M. Hall. 2010. “BEDTools: A Flexible Suite of Utilities for Comparing Genomic Features.” Bioinformatics 26 (6): 841–42. https://doi.org/10.1093/bioinformatics/btq033.
Robinson, Mark D, Davis J McCarthy, and Gordon K Smyth. 2010. “edgeR: A Bioconductor Package for Differential Expression Analysis of Digital Gene Expression Data.” Bioinformatics 26 (1): 139–40. https://doi.org/10.1093/bioinformatics/btp616.