Companion to What They Don't Teach You in Bioinformatics
The part of bioinformatics that isn't the tools.
Every course teaches Seurat, DESeq2, and the Unix commands. This site is about the other half: knowing when a result is wrong, which tool to trust for which job, and how to move data between formats without quietly breaking it.
1 pages
Sanity-check guides
How to tell when an analysis is lying to you, assay by assay: batch effects, doublets, sample swaps, misleading UMAPs, and what to do once you find them.
1 pages
Tool comparisons
DESeq2 or edgeR. Seurat or Scanpy. STAR or salmon. One recommendation per pair, defended, with the cases where the other tool wins.
2 pages
File-format conversions
The exact command, the version it was checked against, and the coordinate, strand, and naming traps that silently corrupt the output.
2 pages
Glossary
Definitions written for people who have to use the term tomorrow, organised by the book's thirteen chapters.
Recently added
- How to Convert h5ad to Seurat object (Without Losing Your Metadata)
anndataR and capseuratconverter handle the transpose and slot mapping for you; deciding which layer actually becomes your counts slot is still on you.
- How to Detect Batch Effects in Bulk RNA-seq
A PCA plot that separates by prep date instead of treatment is telling you the truth about your experiment, not a bug to plot around.
- DESeq2 vs edgeR: Which One Should You Use?
Same negative-binomial model family, different normalization and dispersion philosophy, and that difference decides which one protects you when replicate numbers are small.
- How to Convert GTF to BED (and Keep Your Coordinates Right)
gtf2bed subtracts one from the start coordinate for you; a naive awk one-liner won't, and that gap costs you a silent off-by-one bug three steps downstream.