3 posts
A working guide to taking raw RNA-seq counts from your own samples through filtering, effective-length correction, TMM or median-of-ratios scaling, and variance stabilization, with the diagnostics that tell you whether the normalization held.
A practical walkthrough of differential expression analysis in R, from transcript quantification through DESeq2 and limma models, with the design decisions and failure modes that determine whether the gene list means anything.
A post hoc |log2FC| > 1 filter is the wrong tool. Test against a fold-change threshold directly with DESeq2's lfcThreshold or edgeR's glmTreat, shrink effect sizes before ranking, and pick the threshold from your own replicate structure.