simpleRNASeq

Let RNA-seq analysis simple and easy to repeat!

Description

simpleRNASeq mainly consists of differentially gene expression (DEG) analysis and alternative splicing (DAS) analysis, followed by downstream data visualization and others.

install

You can use devtools to install simpleRNASeq

devtools::install_github('git@github.com:LiangShaw/simpleRNASeq.git')

depedent library

• tidyverse. A meta-package. Please install it yourself.
• DESeq2. For differential experssion analysis. Please install it yourself. If don't use, no need to install.
• ggplot2. For plot. Automatically installed.
• ggsci and ggprism. For plotting DAS volcano plot. Automatically installed.

function Usage

Firstly, import simpleRNASeq and other dependent libraries:

library(simpleRNASeq)
library(tidyverse)
library(DESeq2) # if used

you can type help(function) in R console to view the function help document.

EasyDESeq

You can use software featureCounts to obtain read number for genes.

ls align/*bam | xargs featureCounts -a annotation.gtf -o gene.readcount.txt -t exon -g gene_name -s

and reshape the output,

cat gene.readcount.txt | awk 'NR>1' | sed 's|align/||g' | sed 's|.sorted.bam||g' 

Make use of DESeq2 R package and integrate all the steps into only one.

read count table containing read numbers for control and treatment samples (control at first):

• count of control rep1
• count of control rep2
• count of control repN
• count of treatment rep1
• count of treatment rep2
• count of treatment repN

EasyDESeq(count_tab,tlabel='treatment',clabel='control',tRepN=3,cRepN=3,pthre=0.05,foldchange=1)

you will get a list containing a DESeq2 result and a scale factor dataframe.

DESeq_to_volcano_plot

provide a table containing three columns at least:

• pvalue
• padj
• log2FoldChange

You can set the confidence type (P value or adjusted P value ), confidence threshold and fold change threshold.
And set the colors for decrease and increase as you like.

DESeq_to_volcano_plot(
    tab,pvalue.thres=1,padj.thres=0.05,log2fc.thres=1,
    volcano.title='Gene expression change (treat vs ctrl)',
    yaxis='padj', inc.color='red',dec.color='blue',ns.color='grey60')

You will get a list containing

• a table with change annotation like:

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj	change	yvalue
PERM1	24.39	-1.942	0.634	-3.061	0.0022	0.006	dec	2.2210
ISG15	175.792	-1.137	0.202	-5.603	2.1059e-08	1.082e-07	dec	6.965
TAS1R3	101.24	-1.054	0.258	-4.0738	4.623e-05	0.000162	dec	3.7902

• and a volcano plot like:

rmats_to_volcano_plot

provide a table containing three columns at least:

• PValue
• FDR
• IncLevelDifference

You can set the confidence type (P value or FDR ), confidence threshold and threshold for inclusion lelvel difference (delta PSI).
And set the colors for decrease and increase as you like.

rmats_to_volcano_plot(
    tab,PValue.thres=0.05,FDR.thres=0.05,deltaPSI.thres=0.05,
    volcano.title='PSI change (treat vs ctrl)',
    yaxis='FDR', inc.color='red',dec.color='blue',ns.color='grey60')

You will get a list containing

• a table with change annotation
• a volcano plot (below)

- and a violin plot

readcount_to_TPM

Transfer read count table into TPM value

readcount_to_TPM(readcount.tab)

Table contains:

1. Geneid (or other markers)
2. Length
3. read count for sample1
4. read count for sample2
5. ......

*merge_similar_terms (test version)

Deduplicate GO terms for GO enrichment result from R package gprofiler2.

other scripts

There are some mini shell scripts (in src/) for running Rmats and intergrating the result.

Contributing

Pull requests are welcome.
For major changes, please open an issue first to discuss what you would like to change.

👏👏👏 Welcome more practical tools to join in simpleRNASeq.