The problem. To compare protein abundance across samples by mass spectrometry, the reliable route was chemical labelling (isotope tags), which is costly and limits sample number. Label-free quantification is cheaper and unlimited, but naive intensity comparison is noisy: run-to-run variation and missing values wreck the ratios you actually want.

The idea. MaxLFQ, built into MaxQuant, computes relative abundances from pairwise peptide ratios — extracting the maximum reliable ratio information across samples — and defers normalisation so it doesn’t distort those ratios. The result is label-free quantities accurate enough to stand in for labelled methods across large sample sets.

Why it matters. This is the proteomics analogue of the count-normalisation problem I know from RNA-seq: how do you make abundances comparable across runs of differing total signal? Seeing DESeq’s “model the systematic variation” instinct reappear in mass spec — different data, same discipline — is exactly the cross-modality pattern this reading list keeps surfacing. Proteomics has its own version of every RNA-seq problem.

Verdict. Foundational for quantitative proteomics and still the standard label-free approach. Read it right after MaxQuant (yesterday) — identification then quantification — and note how much it rhymes with the DE normalisation I already do on the RNA side.