Last updated: 2021-02-16

Checks: 6 1

Knit directory: Mouse_PRKO_RNAseq_bulk/

This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

The command set.seed(20210216) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

Using absolute paths to the files within your workflowr project makes it difficult for you and others to run your code on a different machine. Change the absolute path(s) below to the suggested relative path(s) to make your code more reproducible.

absolute relative
/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Mouse_PRKO_RNAseq_bulk/output/mrna_fulllen_pe_strrev_q30.mx.PRKO.all.fix_filt output/mrna_fulllen_pe_strrev_q30.mx.PRKO.all.fix_filt
/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Mouse_PRKO_RNAseq_bulk/output/20200211_PRKO_RNA_samplesheet.txt output/20200211_PRKO_RNA_samplesheet.txt

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version 7f1a156. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


Ignored files:
    Ignored:    .Rproj.user/

Untracked files:
    Untracked:  Mus_musculus.GRCm38.96.fulllength.saf
    Untracked:  analysis/00.WorkFlowR_setting.R
    Untracked:  header.sam
    Untracked:  logCPM_mrna_fulllen_pe_strrev_q30.mx.PRKO.all.fix_filt.csv
    Untracked:  output/20200211_PRKO_RNA_samplesheet.txt
    Untracked:  output/mrna_fulllen_pe_strrev_q30.mx.PRKO.all.fix_filt
    Untracked:  output/mrna_fulllen_pe_strrev_q30.mx.PRKO.unfiltered
    Untracked:  output/mrna_fulllen_pe_strrev_q30.mx.chr

Unstaged changes:
    Modified:   analysis/index.Rmd

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.


These are the previous versions of the repository in which changes were made to the R Markdown (analysis/03.QC_and_CPM.Rmd) and HTML (docs/03.QC_and_CPM.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
Rmd 7f1a156 evangelynsim 2021-02-16 wflow_publish(c(“analysis/01.Generate_reference_genome.Rmd”,

Introduction

In the GEO submission 2 processed files were uploaded.

  1. mrna_fulllen_pe_strrev_q30.mx.PRKO.unfiltered
  2. mrna_fulllen_pe_strrev_q30.mx.PRKO.all.fix_filt

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: limma
library(limma)
library(Glimma)
library(gplots)

Attaching package: 'gplots'
The following object is masked from 'package:stats':

    lowess

Count per million reads

rm1 <- read.delim("/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Mouse_PRKO_RNAseq_bulk/output/mrna_fulllen_pe_strrev_q30.mx.PRKO.all.fix_filt", row.names = 1)

info = read.delim("/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/GITHUB/Mouse_PRKO_RNAseq_bulk/output/20200211_PRKO_RNA_samplesheet.txt", header = TRUE, sep = "\t")
info$ID = gsub("-",".",info$ID)

names(rm1) = info$ID[match(names(rm1),info$ID)]

m = match(info$ID,names(rm1))
rm2 = rm1[,m]
rm1 = rm2

###calculate cpm
mycpm = cpm(rm1)

summary(mycpm)
   PR.KO.F.1          PR.KO.F.2           PR.KO.F.3          PR.KO.F.4        
 Min.   :    0.00   Min.   :    0.000   Min.   :    0.00   Min.   :    0.000  
 1st Qu.:    1.45   1st Qu.:    1.679   1st Qu.:    0.80   1st Qu.:    0.821  
 Median :    8.08   Median :    8.667   Median :    5.89   Median :    5.969  
 Mean   :   60.20   Mean   :   60.205   Mean   :   60.20   Mean   :   60.205  
 3rd Qu.:   33.38   3rd Qu.:   35.712   3rd Qu.:   30.41   3rd Qu.:   30.841  
 Max.   :41591.39   Max.   :26979.638   Max.   :38634.02   Max.   :30994.242  
   PR.KO.M.1          PR.KO.M.2          PR.KO.M.3          PR.KO.M.4       
 Min.   :    0.00   Min.   :    0.01   Min.   :    0.00   Min.   :    0.00  
 1st Qu.:    1.56   1st Qu.:    1.53   1st Qu.:    0.85   1st Qu.:    0.97  
 Median :    8.27   Median :    8.25   Median :    6.31   Median :    6.68  
 Mean   :   60.20   Mean   :   60.20   Mean   :   60.20   Mean   :   60.20  
 3rd Qu.:   34.53   3rd Qu.:   33.92   3rd Qu.:   31.03   3rd Qu.:   30.76  
 Max.   :36859.69   Max.   :36011.74   Max.   :39536.31   Max.   :39661.96  
   PR.WT.F.1          PR.WT.F.2          PR.WT.F.3          PR.WT.M.1       
 Min.   :    0.00   Min.   :    0.00   Min.   :    0.00   Min.   :    0.02  
 1st Qu.:    1.56   1st Qu.:    0.87   1st Qu.:    0.99   1st Qu.:    1.68  
 Median :    8.33   Median :    5.82   Median :    6.91   Median :    8.98  
 Mean   :   60.20   Mean   :   60.20   Mean   :   60.20   Mean   :   60.20  
 3rd Qu.:   34.04   3rd Qu.:   29.23   3rd Qu.:   32.86   3rd Qu.:   35.43  
 Max.   :42162.06   Max.   :33512.06   Max.   :35055.03   Max.   :41445.30  
   PR.WT.M.2          PR.WT.M.3          PR.WT.M.4       
 Min.   :    0.00   Min.   :    0.00   Min.   :    0.00  
 1st Qu.:    1.01   1st Qu.:    0.71   1st Qu.:    0.96  
 Median :    6.16   Median :    5.39   Median :    6.99  
 Mean   :   60.20   Mean   :   60.20   Mean   :   60.20  
 3rd Qu.:   30.23   3rd Qu.:   28.98   3rd Qu.:   31.87  
 Max.   :32040.19   Max.   :32678.54   Max.   :37133.85  
x <- DGEList(rm1)

names(x)
[1] "counts"  "samples"
logcountsx = cpm(x, log = T)

write.csv(logcountsx, "logCPM_mrna_fulllen_pe_strrev_q30.mx.PRKO.all.fix_filt.csv")

barplot(x$samples$lib.size, names=colnames(x), las=2, col = c("maroon1","turquoise1","red","royalblue1")[info$BinSex], main = "Library size")

boxplot(logcountsx, xlab="", ylab="Log2 counts per million", las=2, col = c("maroon1","turquoise1","red","royalblue1")[info$BinSex])
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