4.2 Extracting Results

results() extracts the Wald test output for a given contrast. By default DESeq2 applies independent filtering — it removes genes with very low mean counts before multiple testing correction, which increases power to detect DE genes at a given FDR threshold.

We set alpha = 0.05 to optimise filtering for a 5% FDR cutoff.

res <- results(dds,
               contrast = c("condition", "treatment", "control"),
               alpha    = 0.05)

summary(res)

## 
## out of 3698 with nonzero total read count
## adjusted p-value < 0.05
## LFC > 0 (up)       : 755, 20%
## LFC < 0 (down)     : 850, 23%
## outliers [1]       : 0, 0%
## low counts [2]     : 0, 0%
## (mean count < 5)
## [1] see 'cooksCutoff' argument of ?results
## [2] see 'independentFiltering' argument of ?results

The results table contains one row per gene with the following columns:

Column	Description
baseMean	Mean normalised count across all samples
log2FoldChange	log2(treatment / control)
lfcSE	Standard error of the log2FC estimate
stat	Wald statistic
pvalue	Raw p-value
padj	Benjamini–Hochberg adjusted p-value

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