Hi, I am working on small RNA-seq data and want to identify differentially expressed miRNAs. I know how to do it with DESeq2 and I have got 8 miRNAs as differentially expressed. But I have seen that some authors also do background correction (BC) before applying DESeq2 on raw count data. Background correction is an approach in which those miRNAs are filtered whose sum of counts are less than specified threshold (let's say 5). This reduce the variance in the data and remove all those miRNAs with very poor expression value. Now, when I apply background correction, I am getting different results (in new result, some miRNAs are common with deseq2 result without BC and some are different). My question is which result I should trust and consider for downstream analysis and is BC really necessary before applying DESeq2 analysis in small RNA-seq data.