kallisto_DESeq2.r

In sarangian/RNASeqDEA: Differential Expression Analysis based on the read count data generated by either of Salmon, Kallisto, featureCounts and perform statistical analysis to discover quantitative changes in expression levels between two different experimental groups

#!/usr/bin/env Rscript
################################################################################
### R script to compare two different conditions with kallisto and DESeq2 packages
### Aditya Narayan Sarangi
### Designed to be executed with bulkRNASeqPIPE
################################################################################

rm(list=ls())                                        # remove all the objects from the R session
suppressMessages(library(rnaseqdea))
suppressMessages(library(DESeq2))
suppressMessages(library(DT))
suppressMessages(library(ggplot2))
suppressMessages(library(gplots))
suppressMessages(library(EnhancedVolcano))
suppressMessages(library(GenomicFeatures))
suppressMessages(library(regionReport))
suppressMessages(library(DEFormats))
suppressMessages(library(RColorBrewer))
suppressMessages(library(pheatmap))
suppressMessages(library(dplyr))
suppressMessages(library(colorspace))
suppressMessages(library(optparse))
suppressMessages(library(scales))
suppressMessages(library(readr)) 
suppressMessages(library(rhdf5))
suppressMessages(library(tximport))


# to run the script in command lines

# options list with associated default value.
option_list <- list( 
make_option(c("-P", "--projectName"),
			default=basename(getwd()),
			dest="projectName",
			help="name of the project used for storing images and tables [default: name of the current directory]."),

make_option(c("-R", "--reportName"),
			default="Kallisto_DESeq2_HTML_Report",
			dest="reportName",
			help="name of the project used for the report [default: name of the current directory]."),


make_option(c("-t", "--targetFile"),
			default="target.txt",
			dest="targetFile",
			help="path to the design/target file [default: %default]."),

make_option(c("-T", "--templateFile"),
			dest="templateFile",
			help="path to the R markdown Template file"),

make_option(c("-G", "--tx2geneDirectory"),
			dest="tx2geneDirectory",
			help="path to the tx2gene Directory."),

make_option(c("-q", "--quantDir"),
			dest="quantDir",
			help="path to the directory containing the Kallisto Quantification files"),

	
make_option(c("-v", "--varInt"),
			default="group",
			dest="varInt", 
			help="factor of interest [default: %default]"),

make_option(c("-c", "--condRef"),
			default="WT",
			dest="condRef",
			help="reference biological condition [default: %default]"),

make_option(c("-b", "--batch"),
			default=NULL,
			dest="batch",
			help="blocking factor [default: %default] or \"batch\" for example"),

make_option(c("-f", "--fitType"),
			default="parametric",
			dest="fitType", 
			help="mean-variance relationship: [default: %default],local or mean"),

make_option(c("-a", "--alpha"),
			default=0.05,
			dest="alpha", 
			help="threshold of statistical significance [default: %default]"),

make_option(c("-p", "--pAdjustMethod"),
			default="BH",
			dest="pAdjustMethod", 
			help="p-value adjustment method: \"BH\" or \"BY\" [default: %default]"),


make_option(c("-l", "--locfunc"),
			default="median",
			dest="locfunc", 
			help="median or shorth to estimate the size factors [default: %default]")

)

# now parse the command line to check which option is given and get associated values
parser <- OptionParser(usage="usage: %prog [options]",
					   option_list=option_list, 
					   description="Compare two biological conditions with Kallisto and DESeq2.",
					   epilogue="For comments, bug reports etc... please contact STLAb CSIR-IICB")
opt <- parse_args(parser, args=commandArgs(trailingOnly=TRUE), positional_arguments=0)$options



#Check mandetory inputs 
if ( is.null(opt$targetFile) ) {
  stop("--sample groupfile file / target file must be provided. See script usage (--help)")
}

if ( is.null(opt$quantDir) ) {
  stop("--path to the directory containing the Kallisto Quantification files must be provided. See script usage (--help)")
}

if ( is.null(opt$tx2geneDirectory) ) {
  stop("--tx2geneDirectory folder path must be provided. See script usage (--help)")
}
if ( is.null(opt$condRef) ) {
  stop("--reference biological condition name must be provided. See script usage (--help)")
}





# get options and arguments
workDir <- getwd()
projectName <- opt$projectName 
reportName <-opt$reportName                      # name of the project
targetFile <- opt$targetFile 
templateFile <- opt$templateFile                        # path to the design/target file   
tx2geneDirectory <- opt$tx2geneDirectory             # path to the tx2gene Directory
quantDir <- opt$quantDir                             # path to the directory containing salmon quantification files
varInt <- opt$varInt                                 # factor of interest
condRef <- opt$condRef                               # reference biological condition
batch <- opt$batch                                   # blocking factor: NULL (default) or "batch" for example
fitType <- opt$fitType                               # mean-variance relationship: "parametric" (default), "local" or "mean"
alpha <- as.numeric(opt$alpha)                       # threshold of statistical significance
pAdjustMethod <- opt$pAdjustMethod                   # p-value adjustment method: "BH" (default) or "BY"
locfunc <- opt$locfunc                               # "median" (default) or "shorth" to estimate the size factors
				

 print(paste("workDir", workDir))
 print(paste("projectName", projectName))
 print(paste("reportName", reportName))
 print(paste("targetFile", targetFile))
 print(paste("quantDir", quantDir))
 print(paste("varInt", varInt))
 print(paste("condRef", condRef))
 print(paste("batch", batch))
 print(paste("fitType", fitType))
 print(paste("alpha", alpha))
 print(paste("pAdjustMethod", pAdjustMethod))
 print(paste("locfunc", locfunc))

################################################################################
###                             running script                               ###
################################################################################
# setwd(workDir)
#dir.create(projectName, showWarnings = FALSE, recursive = TRUE)

#imageFolder <- paste0(projectName,"/figures/")
#tableFolder <- paste0(projectName,"/tables/")

#dir.create(imageFolder, showWarnings = FALSE, recursive = TRUE)
dir.create("tables", showWarnings = FALSE, recursive = TRUE)


#source("/opt/RNASeqPIPE/tools/utility/load.TargetFile.R")
#source("/opt/RNASeqPIPE/tools/utility/run.DESeq2_trans.r")
#source("/opt/RNASeqPIPE/tools/utility/exportResults.DESeq2.R")

#plots
					   
# loading target file
target <- loadTargetFile(targetFile=targetFile, varInt=varInt, condRef=condRef, batch=batch)
#names(target$files)
print (target)
#loading counts

sampledata = read.table(targetFile, header = TRUE, sep='\t')

print (sampledata)
samplenames = sampledata$samples
print (samplenames)

files <- file.path(quantDir, 'kallisto_quant', target$samples, "abundance.h5")

#print ("file names:",files)

kallisto_dname <- dirname(files)
kallisto_file_names <- basename(kallisto_dname)
names(files) <- kallisto_file_names
print (files)


tx2gene <- read_csv(file.path(tx2geneDirectory, "tx2gene.csv"))

txi.kallisto <- tximport(files, type="kallisto", tx2gene=tx2gene)

countdata <- txi.kallisto$counts 


#Add header (sample names to count data)
#sampledata = read.table(targetFile, header = TRUE)
#samplenames = sampledata[,"label"]
#colnames(countdata) = samplenames
#head(countdata) 



#analysis with DESeq2
out.DESeq2 <- run.DESeq2_trans(counts=txi.kallisto, target=target, varInt=varInt, batch=batch,
                         locfunc=locfunc, fitType=fitType, pAdjustMethod=pAdjustMethod,
                         alpha=alpha)
#####
dds <- out.DESeq2$dds
res <- results(dds)
dds <- dds[ rowSums(counts(dds)) > 0, ]


coldata <- colData(dds)
intgroup<- colnames(coldata[c(2,3)])

#coldata
#intgroup


dds.rld.trans <- rlog(dds, blind=FALSE)


sampleDists <- as.matrix(dist(t(assay(dds.rld.trans))))

####################################################################################
exportResults.DESeq2(out.DESeq2, group=unique(target[,varInt]), alpha=alpha)
####################################################################################

save.image(file=paste0(reportName, ".RData"))

report <- DESeq2Report(dds, projectName, intgroup, outdir = reportName,  output = 'index', nBest = 50000, nBestFeatures = 20, template = templateFile)

if(interactive()) {
    browseURL(report)
}