[BioC] Deseq-2 help

Mubarak hussain Syed mosvey at gmail.com
Sat Mar 15 21:16:25 CET 2014

Hello , 

I am new to Deseq2 package and ,I am interested in differential gene expression calculations. I have two conditions Condition a (T) and Condition b (P), 
From the Deseq-2 results after using the below mentioned commands, I get a long list of differentially expressed gene, more than 1000 unregulated and 
more than thousand down regulated. 

countsTable <- read.delim ("counts.txt", header=TRUE, row.names=1)
pdata = data.frame(condition = factor(c( "T", "T", "T", "P", "P", "P", "P"))) # Three total vs four pure samples
library (DESeq2)
dds <- DESeqDataSetFromMatrix(countData=countsTable, colData = pdata, design=~condition)
colData(dds)$condition <- relevel(colData(dds)$condition, "T")
dds <- DESeq(dds)
results <- results(dds)
results <- as.data.frame(results)
sig.up.results <- results[which(results$padj < 0.05 & results$log2FoldChange > 0),]
sig.down.results <- results[which(results$padj < 0.05 & results$log2FoldChange < 0),]
sig.results <- results[which(results$padj < 0.05),]
sig.results <- sig.results[order(sig.results$log2FoldChange, decreasing=TRUE),]
plotMA(dds, pvalCutoff=0.05)
write.table (sig.results, file= "DESeq2_Sigresultsfiltered_48_96.txt", sep= "\t ", row.names=TRUE, col.names=TRUE)
write.table (results, file= "DESeq2_allresults_filtered_48_96.txt", sep= "\t ", col.names=TRUE)

Do you have any suggestions about my experiment or commands I am using to narrow down 
 my differential gene list. Do I ned to filter low count genes or highly expressed house keeping genes, I appreciate your time.

best regards

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