Version Compatibility

Reference examples tested with: pyOpenMS 3.1+, pandas 2.2+, numpy 1.26+

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

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

Peptide Identification -- Confidence Is a Property of a Ranked List, Not a Single PSM

"Identify peptides from my MS/MS spectra" -> Match tandem mass spectra against a protein database, then control false discovery rate by target-decoy competition and act on a q-value -- because a raw match score is meaningless in isolation; only the list-level error rate is interpretable.

• Python: pyopenms.SimpleSearchEngineAlgorithm().search(...) for in-process database search, FalseDiscoveryRate for q-values
• CLI: comet, msfragger, sage, MSGFPlus for high-throughput database searching, percolator/mokapot for rescoring
• R: mzID::mzID() + flatten() or mzR::openIDfile() + psms() to read mzIdentML search results

Scope: this skill owns spectrum-to-peptide matching and PSM/peptide-level FDR. Protein grouping and protein-level (picked) FDR -> protein-inference. PTM site localization and open-search mod discovery follow-up -> ptm-analysis. DIA peptide-centric extraction and scoring -> dia-analysis. FDR-filtered IDs feeding intensities -> quantification. mzML/raw loading -> data-import. OUT OF SCOPE: protein inference, PTM localization scoring, DIA peptide-centric pipelines, label-free/TMT quantification.