Version Compatibility

Reference examples tested with: pyOpenMS 3.1+, pandas 2.2+, numpy 1.26+, MSnbase 2.28+

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.

Mass Spectrometry Data Import -- Inheriting the Acquisition Contract and Stripping the Bookkeeping

"Load my mass spec data into Python" -> Parse spectra or a search-engine table AND immediately enforce two contracts -- which quant column carries real biology, and which rows are search-engine bookkeeping that must be deleted -- because the same proteinGroups.txt yields different conclusions depending on the column read and the rows kept.

• Python: pyopenms.MzMLFile().load(path, exp) for raw spectra; pandas.read_csv(sep='\t') for MaxQuant; pandas.read_parquet for DIA-NN
• R: Spectra::Spectra() / QFeatures::readQFeatures() for raw and quantified data (MSnbase still works but is in maintenance mode)

Scope: this skill owns reading spectra/search outputs into memory, deleting decoy/contaminant/site-only rows, picking the correct quant column, and characterizing missingness. Format conversion (RAW -> mzML) -> peptide-identification. MaxLFQ/TMT reporter quant computation -> quantification. Protein-group parsimony -> protein-inference. Normalization and imputation -> differential-abundance and expression-matrix/normalization. OUT OF SCOPE: statistical testing, batch correction, and the actual imputation step (this skill only diagnoses the missingness so the right imputer is chosen later).