2.10 Differential expression analysis
Estimated read counts from featureCounts were used as input to functions in the DESeq2 R package (Love et al. 2014) to generate log2 differential expression fold-difference estimates. Transcripts with less than 10 reads summed across all samples were removed from the analysis. Genes with adjusted p-value less than 5% (according to the FDR method from Benjamini-Hochberg, 1995) were declared differentially expressed. A log2FoldChange value greater than zero indicates an upregulation in FW compared to SW and a log2FoldChange value less than 0 indicates a downregulation in FW compared to SW. In order to explore the variability within our experiment, hierarchical clustering and PCA were performed after Variance Stabilizing Transformation (VST) of the count data.