tooluniverse-proteomics-analysis

Analyze mass spectrometry proteomics data including protein quantification, differential expression, post-translational modifications (PTMs), and protein-protein interactions. Processes MaxQuant, Spectronaut, DIA-NN, and other MS platform outputs. Performs normalization, statistical analysis, pathway enrichment, and integration with transcriptomics. Use when analyzing proteomics data, comparing protein abundance between conditions, identifying PTM changes, studying protein complexes, integrating protein and RNA data, discovering protein biomarkers, or conducting quantitative proteomics experiments.

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Install skill "tooluniverse-proteomics-analysis" with this command: npx skills add mims-harvard/tooluniverse/mims-harvard-tooluniverse-tooluniverse-proteomics-analysis

Proteomics Analysis

Comprehensive analysis of mass spectrometry-based proteomics data from protein identification through quantification, differential expression, post-translational modifications, and systems-level interpretation.

When to Use This Skill

Triggers: User has proteomics MS output files, asks about protein abundance/expression, differential protein expression, PTM analysis, protein-RNA correlation, multi-omics integration involving proteomics, protein complex/interaction analysis, or proteomics biomarker discovery.

Core Capabilities

CapabilityDescription
Data ImportMaxQuant, Spectronaut, DIA-NN, Proteome Discoverer, FragPipe outputs
Quality ControlMissing value analysis, intensity distributions, sample clustering
NormalizationMedian, quantile, TMM, VSN normalization methods
ImputationMinProb, KNN, QRILC for missing values
Differential ExpressionLimma, DEP, MSstats for statistical testing
PTM AnalysisPhospho-site localization, PTM enrichment, kinase prediction
Protein-RNA IntegrationCorrelation analysis, translation efficiency
Pathway EnrichmentOver-representation and GSEA for protein sets
PPI AnalysisProtein complex detection, interaction networks via STRING/IntAct
ReportingComprehensive reports with volcano plots, heatmaps, pathway diagrams

Workflow Overview

Input: MS Proteomics Data
    |
Phase 1: Data Import & QC
Phase 2: Preprocessing (filter, impute, normalize)
Phase 3: Differential Expression Analysis
Phase 4: PTM Analysis (if applicable)
Phase 5: Functional Enrichment (GO, KEGG, Reactome)
Phase 6: Protein-Protein Interactions (STRING networks)
Phase 7: Multi-Omics Integration (optional, protein-RNA correlation)
Phase 8: Generate Report

See PHASE_DETAILS.md for detailed procedures per phase.

Integration with ToolUniverse

SkillUsed ForPhase
tooluniverse-gene-enrichmentPathway enrichmentPhase 5
tooluniverse-protein-interactionsPPI networksPhase 6
tooluniverse-rnaseq-deseq2RNA-seq for integrationPhase 7
tooluniverse-multi-omics-integrationCross-omics analysisPhase 7
tooluniverse-target-researchProtein annotationPhase 8

Quantified Minimums

ComponentRequirement
Proteins quantifiedAt least 500 proteins
ReplicatesAt least 3 per condition
Filtering2+ unique peptides per protein
Statistical testlimma or t-test with multiple testing correction
Pathway enrichmentAt least one method (GO, KEGG, or Reactome)
ReportSummary, QC, DE results, pathways, visualizations

Limitations

  • Platform-specific: Optimized for MS-based proteomics (not Western blot quantification)
  • Missing values: High missing rate (>50% per protein) limits statistical power
  • PTM analysis: Requires enrichment protocols for comprehensive PTM profiling
  • Absolute quantification: Relative abundance only (unless TMT/SILAC used)
  • Protein isoforms: Typically collapsed to gene level
  • Dynamic range: MS has limited dynamic range vs mRNA sequencing

References

Methods: MaxQuant (doi:10.1038/nbt.1511), Limma for proteomics (doi:10.1093/nar/gkv007), DEP workflow (doi:10.1038/nprot.2018.107)

Databases: STRING, PhosphoSitePlus, CORUM

Reference Files

  • PHASE_DETAILS.md - Detailed procedures for each analysis phase, including report template

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