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login1$ R
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> library("DESeq")
> combined = read.csv("combined.csv", header=T, row.names=1)
> design <- data.frame(
row.names = colnames( combined ),
condition = c( "Anc", "Anc", "EL", "EL", "EW", "EW"),
libType = c( "single-end", "single-end", "single-end",
"single-end", "single-end", "single-end" ) )
> design
> conds <- factor(design$condition)
> cds <- newCountDataSet( combined, conds )
> cds <- estimateSizeFactors( cds )
> sizeFactors( cds )
> res <- nbinomTest( cds, "EL", "EW" )
> write.csv(res, "EL-vs-EW.csv")
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Additional
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Points
- In an actual RNAseq analysis, you might want to trim stray adaptor sequences from your data using a tool like the FASTX-Toolkit or FAR before aligning.