Version Compatibility

Reference examples tested with: MSstatsPTM 2.4+, pandas 2.2+, numpy 1.26+, scipy 1.12+

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.

PTM and Phosphoproteomics Analysis -- Three Inference Layers Stacked on a Biased Extraction

"Find the regulated phosphosites in my enriched samples" -> Localize each modification, then test whether its abundance change survives subtracting the protein-level change -- because a PTM result is three separate inferences (enrichment, localization, quantification) and each fails silently if the layer below is treated as solved.

• R: MSstatsPTM::groupComparisonPTM() for protein-adjusted site testing (the load-bearing tool)
• Python: pandas to expand MaxQuant Phospho (STY)Sites multiplicity and filter localization probability
• R: KSEAapp / PTM-SEA (ssGSEA2.0) for kinase-activity inference from the site fold-changes

Scope: this skill OWNS enrichment-chemistry framing, site localization and FLR, multiplicity-resolved site quant, protein-level adjustment, motif analysis, and kinase-activity inference. Peptide identification and open/variable-mod search route to peptide-identification; the underlying protein-level (unenriched) quant routes to quantification and differential-abundance; DIA acquisition mechanics route to dia-analysis. OUT OF SCOPE: intact-glycopeptide glycan-composition search (pGlyco3/MSFragger-Glyco) and absolute occupancy from three-ratio SILAC are noted but not implemented here.