bio-metabolomics-lipidomics
Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSear…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Use when starting a proteomics analysis with raw or processed MS data. Handles contaminant filtering and missing value assessment.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-proteomics-data-import
Skill Snapshot
Source Doc
Goal: Parse raw mass spectrometry data files into memory for programmatic access.
Approach: Load mzML/mzXML into an MSExperiment object, then iterate spectra by MS level to access peaks and precursor info.
Goal: Import MaxQuant proteinGroups.txt with contaminant and decoy filtering.
Approach: Read the TSV file, remove reverse hits, contaminants, and site-only identifications, then extract intensity columns.
import pandas as pd
protein_groups = pd.read_csv('proteinGroups.txt', sep='\t', low_memory=False)
## Extract intensity columns (LFQ or iBAQ)
intensity_cols = [c for c in protein_groups.columns if c.startswith('LFQ intensity') or c.startswith('iBAQ ')]
if not intensity_cols:
intensity_cols = [c for c in protein_groups.columns if c.startswith('Intensity ') and 'Intensity L' not in c]
intensities = protein_groups[['Protein IDs', 'Gene names'] + intensity_cols]
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