Version Compatibility

Reference examples tested with: pandas 2.2+, numpy 1.26+, scanpy 1.10+, anndata 0.10+, tximport 1.30+, tximeta 1.20+, GenomicFeatures 1.54+, Subread/featureCounts 2.0.6+ (post-v2.0.2 API), STAR 2.7.10+, Salmon 1.10+, kallisto 0.48+, RSEM 1.3.3+, HTSeq 2.0+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name to verify parameters
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Count Matrix Ingestion

"Load my featureCounts / Salmon / STAR output into a count matrix" -> Parse the per-sample quantification, strip metadata, choose the correct strandedness or NumReads column, optionally apply length-bias correction via tximport, and return a gene-by-sample matrix appropriate for the downstream DE tool.

The Single Most Important Modern Insight -- lengthScaledTPM is NOT TPM; the naming has fooled many

tximport(..., countsFromAbundance='lengthScaledTPM') returns a count-scale matrix (sum to library size) with the gene-length bias removed, intended as input to DE tools that cannot accept offsets (limma-voom). The word "TPM" in the option name has misled users into reporting these values as normalized abundance -- they are not.