Hey everybody!
I would like to hear your opinion about using pseudocounts when performing RNA-seq analysis. I have always been following the standard protocol for DESeq2 when analyzing RNA-seq data, using their great guide, but recently a colleague pointed out that I should always add the value 1 to counts of all genes. He mentioned that this will help for those genes which have a count of 0, in order to avoid dealing with negative values after transformation.
I always filter out low counts genes with:
filtered <- rowSums(counts(dds)) >= 10
So I wonder if DESeq2 already deals with pseudocounts by default or if it's required that I perform this step myself.
Thanks!
Thanks you for your answer! So for example I should use pseudo counts when plotting heatmaps, volcano plots, PCA plots, etc.? And when it comes to GSEA, where I use as input the normalised read counts matrix for all genes and replicates, should I also use pseudocounts in that case?
I have not used pcs for anything but preventing taking logs of zeros.