I am working on the RNA-Seq data of bacterial samples including untreated and 2 drug treatment groups (3 replicates each) following the DESeq2 steps. My question is looking at the dispersion plots including fit type parametric and local, can it be inferred that there is less variability among the genes? Also because the results table also gave about 265 statistically significant genes between the control and treatment 1. It seems that with higher mean counts there is a slight increase in dispersion in the fit type local. Kindly share your feedback on understanding this plot.
Code should be placed in three backticks as shown below
ddsObj<- DESeqDataSetFromMatrix(countData = Raw_counts,colData = sampleinfo,design = ~Condition) idx <- rowSums(counts(ddsObj) >10 ) >3 table(idx) ddsObj<-ddsObj[idx,] dds<-DESeq(ddsObj) plotDispEsts(dds) plotDispEsts(dds,fitType = "local") dds$sizeFactor res<-results(dds) res<-res[order(res$padj),]