Hello All,

I am trying to use DESeq, a sample of my data looks like below (X.1 & X.2
are replicates, Y1 & Y2 are replicates).


*GeneNo X.1 X.2 Y.1 Y.2*
gene00001 4 3 3 1
gene00002 17 45 39 30
gene00003 25 40 29 24
gene00004 8 8 9 3
gene00009 1 0 0 0
gene00011 1 2 4 2
gene00012 0 0 0 0
gene00014 17 7 8 21


 I used the following commands to find the differentially expressed genes.
I have two questions,

   1. Are the following commands correct ? or am i missing something?
   2. How can i determine which genes are differentially expressed?
   induced? suppressed? unchanged?



library( "DESeq" )
exampleFile = system.file( "extra/X_Y_Reads.txt", package="DESeq" )
countsTable <- read.delim( exampleFile, header=TRUE, stringsAsFactors=TRUE )
rownames( countsTable ) <- countsTable$gene
countsTable <- countsTable[ , -1 ]
conds <- c( "X","X","Y","Y")
cds <- newCountDataSet( countsTable, conds )

libsizes <- clibsizes <- c(X.1=18143070, X.2=13544150, Y.1=17853990,
Y.2=15038501)
sizeFactors(cds) <- libsizes[-1]
cds <- estimateSizeFactors( cds )
sizeFactors( cds )
cds <- estimateDispersions( cds )
res <- nbinomTest( cds, "X", "Y" )
plot(res$baseMean,res$log2FoldChange,log="x", pch=20, cex=.1,col = ifelse(
res$padj < .001, "red", "black" ) )
resSig <- res[ res$padj < .001, ]
head( resSig[ order(resSig$pval), ] )
write.table(res,"C:\\Users\\OMD\\Desktop\\XY_DEG.txt")

-- 
Thank you,

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