Hello,

After running DESeq and filtering using alpha = 0.05 and lfcThreshold = 1

> dds <- DESeq(dds)
> res.05_1 <- results(dds, alpha = 0.05, lfcThreshold = 1)
> summary(res.05_1)

out of 33402 with nonzero total read count
adjusted p-value < 0.05
LFC > 1.00 (up)    : 964, 2.9%
LFC < -1.00 (down) : 1228, 3.7%
outliers [1]       : 5, 0.015%
low counts [2]     : 4484, 13%
(mean count < 1)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results

How do I extract the 964 upregulated and 1228 downregulated genes? Also, how do I find the information on which sample is the gene expression up or down?

Thank you very much

Nelson

The object returned by results() is a DESeqResults object, built on top of a DataFrame. It acts a lot like a simple data.frame in R.

First take a look at the column names:

res

You will also notice when you print the object like this, that it tells you at the top of the table which sample is in the numerator and which sample is in the denominator of the LFC (log2 fold change).

If you want the upregulated gene rows:

res[which(res$log2FoldChange > 0 & res$padj < .05),]