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Mp_Hosts_non_hosts_DE_exons_R_commands.sh
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Mp_Hosts_non_hosts_DE_exons_R_commands.sh
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R
#inDir = system.file("extdata", package="pasilla")
inDir = '/home/PATH_TO/Desktop/Mp_Hots_nnhost_DE_exon'
countFiles = list.files(inDir, pattern=".exon.counts$", full.names=TRUE)
basename(countFiles)
flattenedFile = list.files(inDir, pattern="gff$", full.names=TRUE)
basename(flattenedFile)
# [1] "treated1fb.txt" "treated2fb.txt" "treated3fb.txt" "untreated1fb.txt"
## [5] "untreated2fb.txt" "untreated3fb.txt" "untreated4fb.txt"
sampleTable = data.frame(row.names =
c("Mp_host_24h_1", "Mp_host_24h_2", "Mp_host_24h_3", "Mp_host_24h_4", "Mp_host_24h_5","Mp_nonhost_24h_1", "Mp_nonhost_24h_2", "Mp_nonhost_24h_3", "Mp_nonhost_24h_4", "Mp_nonhost_24h_5"), condition = c("Mp_host_24h", "Mp_host_24h", "Mp_host_24h", "Mp_host_24h", "Mp_host_24h", "Mp_nonhost_24h", "Mp_nonhost_24h", "Mp_nonhost_24h", "Mp_nonhost_24h", "Mp_nonhost_24h"),libType = c("paired-end", "paired-end", "paired-end", "paired-end", "paired-end", "paired-end", "paired-end", "paired-end", "paired-end", "paired-end"))
sampleTable
#dxd =read.HTSeqCounts(countFiles,sampleData=sampleTable,design= ~ sample + exon + condition:exon,flattenedfile=flattenedFile)
library("DEXSeq")
######################################################################################################
dxd = DEXSeqDataSetFromHTSeq(countFiles,sampleData=sampleTable,design= ~ sample + exon + condition:exon,flattenedfile=flattenedFile)
# create a file with gene name, grep genome.gff | cut -f gene_name > geneIDsinsubset.txt
genesForSubset = read.table(file.path(inDir, "geneIDsinsubset.txt"),stringsAsFactors=FALSE)[[1]]
dxd = dxd[geneIDs( dxd ) %in% genesForSubset,]
colData(dxd)
head( counts(dxd), 5)
head( featureCounts(dxd), 5)
head ( rowRanges(dxd), 3 )
sampleAnnotation( dxd )
####################################################################################################################################################################################
4) normalisation
# can use multiple core if using package BiocParallel, and implemented the BPPARAM
#BPPARAM = MultiCoreParam(workers=3)
# uses DEseq2 method
dxd = estimateSizeFactors( dxd )
# dispersion estimation
dxd = estimateDispersions( dxd)
# multi core
#dxd = estimateDispersions( dxd, BPPARAM=BPPARAM)
plotDispEsts( dxd )
# test for DE (exon) expression)
dxd = testForDEU( dxd )
# multi core
dxd = testForDEU( dxd, BPPARAM=BPPARAM)
# estimate fold change
dxd = estimateExonFoldChanges( dxd, fitExpToVar="condition")
dxr1 = DEXSeqResults( dxd )
write.table(dxr1, file = "Dexseq_results.out", append = FALSE, quote = TRUE, sep = "\t",
eol = "\n", na = "NA", dec = ".", row.names = TRUE,
col.names = TRUE, qmethod = c("escape", "double"),
fileEncoding = "")
dxr1
#From this object, we can ask how many genes are signi cant with a false discovery rate of 5%:
#table ( dxr1$padj < 0.05 )
#From this object, we can ask how many genes are signi cant with a false discovery rate of 1%:
table ( dxr1$padj < 0.01 )
# ask how many genes are a ected (FDR 0.001)
table ( tapply( dxr1$padj < 0.001, dxr1$groupID, any ) )
plotMA(dxr1, cex=0.8)
####################################################################################################################################################################################
4) visualization
# put in the appropriate gene name of interest!!!!!!!
#plotDEXSeq( dxr1, "FBgn0010909", legend=TRUE, cex.axis=1.2, cex=1.3, lwd=2 )
plotDEXSeq( dxr1, "1005", legend=TRUE, cex.axis=1.2, cex=1.3, lwd=2 )
#another
# put in the appropriate gene name of interest!!!!!!!
#plotDEXSeq( dxr2, "FBgn0010909", displayTranscripts=TRUE, legend=TRUE,cex.axis=1.2, cex=1.3, lwd=2 )
plotDEXSeq( dxr1, "1005", displayTranscripts=TRUE, legend=TRUE,cex.axis=1.2, cex=1.3, lwd=2 )
# to display it with the normalised counts.
#plotDEXSeq( dxr2, "FBgn0010909", expression=FALSE, norCounts=TRUE,legend=TRUE, cex.axis=1.2, cex=1.3, lwd=2)
#plotDEXSeq( dxr2, "FBgn0010909", expression=FALSE, splicing=TRUE,legend=TRUE, cex.axis=1.2, cex=1.3, lwd=2 )
plotDEXSeq( dxr2, "1005", expression=FALSE, splicing=TRUE,legend=TRUE, cex.axis=1.2, cex=1.3, lwd=2 )
# WRITE TO BROWSEABLE HTML USING DEXSeqHTML
#DEXSeqHTML( dxr2, FDR=0.1, color=c("#FF000080", "#0000FF80")
#colour command doesnt work!!!
#DEXSeqHTML( dxr1, FDR=0.001, color=c("#FF000080", "#0000FF80")
DEXSeqHTML( dxr1, FDR=0.01)
#DEXSeqHTML( dxr1, FDR=0.001)