5 posts
A working guide to diagnosing and handling batch effects in bulk RNA-seq, from design and TMM normalization through limma, ComBat-seq, and RUV, with the checks that tell you whether the correction helped.
How to use R and Bioconductor as the annotation, statistics, and integration layer for a personal molecular dataset: VCFs, RNA-seq counts, proteomics, and continuous glucose data, with the parts you should not do in R.
A working pipeline from FASTQ files to gene-level counts, differential expression, and enrichment, using salmon, pytximport, and PyDESeq2, with the failure modes specific to blood RNA from a single person.
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.
A practical guide to building violin plots from bulk and single-cell RNA-seq counts: which normalization to plot, how to set kernel bandwidth and trimming, and how to read the shapes without fooling yourself.