QC filtered sequencing reads (Peaks)
Evangelyn Sim
2/2/2021
Last updated: 2021-02-19
Checks: 6 1
Knit directory: Human_Development_ATACseq_bulk/
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| /group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Human_Development_ATACseq_bulk/output/humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.all.fix_filt.csv | output/humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.all.fix_filt.csv |
| /group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Human_Development_ATACseq_bulk/output/ATACseq_samplesheet.txt | output/ATACseq_samplesheet.txt |
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Introduction
In the GEO submission, 4 processed files (peaks) were uploaded.
- humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.all_unfiltered.csv
- humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.all.fix_filt.csv
- humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.hum.fix_filt.csv
- humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.MvsF.fix_filt.csv
They have been uploaded in the /output folder and will be used below to generate different figures.
Used libraries and functions
library(edgeR)Loading required package: limmalibrary(limma)
library(Glimma)
library(gplots)
Attaching package: 'gplots'The following object is masked from 'package:stats':
lowessCount per million reads
rm1 <- read.csv("/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Human_Development_ATACseq_bulk/output/humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.all.fix_filt.csv", row.names = 1)
info = read.delim("/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Human_Development_ATACseq_bulk/output/ATACseq_samplesheet.txt", header = TRUE, sep = "\t")
m = match(info$ID,names(rm1))
rm2 = rm1[,m]
rm1 = rm2
mycpm = cpm(rm1)
summary(mycpm) Fetal1 Fetal2 Fetal3 Young1
Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 3.148 1st Qu.: 2.700 1st Qu.: 3.038 1st Qu.: 2.512
Median : 5.438 Median : 4.801 Median : 5.298 Median : 4.742
Mean : 10.230 Mean : 10.230 Mean : 10.230 Mean : 10.230
3rd Qu.: 11.735 3rd Qu.: 11.202 3rd Qu.: 11.585 3rd Qu.: 11.556
Max. :2027.691 Max. :2324.248 Max. :1723.871 Max. :1113.559
Young2 Young3 Young4 Adult1
Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 3.235 1st Qu.: 2.798 1st Qu.: 2.379 1st Qu.: 2.075
Median : 5.475 Median : 4.959 Median : 4.559 Median : 4.018
Mean : 10.230 Mean : 10.230 Mean : 10.230 Mean : 10.230
3rd Qu.: 11.780 3rd Qu.: 11.508 3rd Qu.: 11.365 3rd Qu.: 10.508
Max. :2363.268 Max. :2413.537 Max. :1304.316 Max. :995.980
Adult2 Adult3 Adult4 Adult5
Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 2.575 1st Qu.: 3.766 1st Qu.: 2.536 1st Qu.: 2.686
Median : 4.875 Median : 6.162 Median : 4.590 Median : 4.667
Mean : 10.230 Mean : 10.230 Mean : 10.230 Mean : 10.230
3rd Qu.: 11.619 3rd Qu.: 12.051 3rd Qu.: 11.017 3rd Qu.: 10.963
Max. :1665.484 Max. :4331.669 Max. :968.910 Max. :1521.759
Adult6 Adult7 Adult8 Adult9
Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 2.126 1st Qu.: 2.006 1st Qu.: 2.509 1st Qu.: 2.030
Median : 4.285 Median : 4.043 Median : 4.460 Median : 4.228
Mean : 10.230 Mean : 10.230 Mean : 10.230 Mean : 10.230
3rd Qu.: 10.953 3rd Qu.: 10.707 3rd Qu.: 10.872 3rd Qu.: 11.154
Max. :1282.877 Max. :834.229 Max. :1254.172 Max. :1053.526
Adult10 Adult11 Adult12 Adult13
Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 2.337 1st Qu.: 2.640 1st Qu.: 2.332 1st Qu.: 2.963
Median : 4.347 Median : 4.675 Median : 4.296 Median : 5.024
Mean : 10.230 Mean : 10.230 Mean : 10.230 Mean : 10.230
3rd Qu.: 10.704 3rd Qu.: 11.037 3rd Qu.: 10.616 3rd Qu.: 11.142
Max. :1948.646 Max. :1283.103 Max. :2013.372 Max. :2154.891
hiPSCCM1 hiPSCCM2 hiPSCCM3 hiPSCCM4
Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 4.511 1st Qu.: 4.616 1st Qu.: 3.846 1st Qu.: 4.666
Median : 6.626 Median : 6.653 Median : 6.025 Median : 6.820
Mean : 10.230 Mean : 10.230 Mean : 10.230 Mean : 10.230
3rd Qu.: 11.843 3rd Qu.: 11.676 3rd Qu.: 11.409 3rd Qu.: 11.666
Max. :7495.477 Max. :9096.587 Max. :5379.331 Max. :9059.116
hiPSCCM5 hiPSCCM6 hiPSCCM7
Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 4.689 1st Qu.: 4.010 1st Qu.: 4.427
Median : 7.034 Median : 6.626 Median : 6.788
Mean : 10.230 Mean : 10.230 Mean : 10.230
3rd Qu.: 11.904 3rd Qu.: 11.683 3rd Qu.: 11.804
Max. :6804.441 Max. :5309.122 Max. :5240.105 x <- DGEList(rm1)
names(x)[1] "counts" "samples"logcountsx = cpm(x, log = T)
write.csv(logcountsx, file = "/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Human_Development_ATACseq_bulk/output/logCPM_humanATAC_peaks_cov2_rmBL.bed.saf.pe.q30.mx.all.fix_filt.csv")
barplot(x$samples$lib.size, names=colnames(x), las=2, col = c("turquoise1","maroon1","bisque1","purple")[info$Group], main = "Library size")
boxplot(logcountsx, xlab="", ylab="Log2 counts per million", las=2, col = c("turquoise1","maroon1","bisque1","purple")[info$Group])
abline(h=median(logcountsx), col="navy")
sessionInfo()R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS: /hpc/software/installed/R/3.6.1/lib64/R/lib/libRblas.so
LAPACK: /hpc/software/installed/R/3.6.1/lib64/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] gplots_3.1.0 Glimma_1.12.0 edgeR_3.26.8 limma_3.40.6
[5] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.5 pillar_1.4.6 compiler_3.6.1 later_1.1.0.1
[5] git2r_0.27.1 highr_0.8 bitops_1.0-6 tools_3.6.1
[9] digest_0.6.27 jsonlite_1.7.0 evaluate_0.14 lifecycle_0.2.0
[13] tibble_3.0.3 lattice_0.20-41 pkgconfig_2.0.3 rlang_0.4.7
[17] rstudioapi_0.11 yaml_2.2.1 xfun_0.18 stringr_1.4.0
[21] knitr_1.30 caTools_1.18.0 gtools_3.8.2 fs_1.5.0
[25] vctrs_0.3.2 locfit_1.5-9.4 rprojroot_1.3-2 grid_3.6.1
[29] glue_1.4.2 R6_2.5.0 rmarkdown_2.5 magrittr_1.5
[33] whisker_0.4 backports_1.1.10 promises_1.1.1 ellipsis_0.3.1
[37] htmltools_0.5.0 httpuv_1.5.4 KernSmooth_2.23-17 stringi_1.5.3
[41] crayon_1.3.4