Proteomics Data Interpreter: Claude-Assisted Analysis & Troubleshooting
Interpret mass spectrometry proteomics results and diagnose experimental anomalies
What You Can Do
You can submit raw mass spectrometry observations, instrument parameters, or sample preparation details to Claude and receive targeted diagnostic frameworks that explain anomalous results. Claude systematically generates plausible mechanistic explanations for unexpected protein abundance patterns, quantification inconsistencies, and PTM findings—then helps you design minimal, hypothesis-driven troubleshooting experiments to test them.
Features
distinguish real biology from technical artifacts with mechanistic reasoning
understand misaligned peptide ratios and protein fold-changes across replicates
generate hypothesis-driven QC and validation approaches with minimal sample waste
integrate structural biology, biochemistry, and literature insights
balance stringency vs. sensitivity tradeoffs for your specific biological question
evaluate sample prep, instrument drift, normalization, and biological hypotheses
identify confounding variables you may have overlooked
Example Output
Input: "We see 500 proteins with >2-fold change in lipopolysaccharide-treated macrophages, but pathway enrichment is flat. Expected ~50 differentially abundant proteins based on literature."
Claude Output:
- Hypothesis 1 (most likely): Global normalization artifact — check if total protein load or ionization differs between samples
- Hypothesis 2: Real but transient response — LPS-induced proteome is broad at 4h; check timepoint literature
- Hypothesis 3: Sample prep contamination — confirm endotoxin removal; re-run blank controls
- Recommended experiment: Normalize to spike-in standards and reprocess; if fold-changes collapse, normalization was the issue
Input: "Phosphoprotein ratios are inverted between DDA and DIA methods on same sample. Which method is wrong?"
Claude Output:
- DDA may undersample low-abundance phosphopeptides (stochastic sampling bias)
- DIA may have library mismatch for phosphovariant masses
- Distinguish with: Parallel SRM/MRM of 5 phosphosites across both methods; compare reproducibility vs. literature values
What's Included
- SKILL.md instruction file with proteomics-specific prompting framework:
- Troubleshooting decision tree: flowchart matching symptoms to root causes (sample prep, instrumental, computational, biological)
- Diagnostic question template: structured prompts to extract maximum mechanistic insight from Claude
- QC criteria checklist: data validation standards for DDA, DIA, and targeted proteomics
- Experiment design worksheet: hypothesis-ranking framework with power and cost estimation
Who It's For
- Proteomics bioinformaticians — interpret complex MS datasets and troubleshoot quantification anomalies
- Mass spectrometry facility managers — diagnose instrument performance and sample prep issues at scale
- Pharmaceutical R&D scientists — validate biomarker discovery and optimize protein abundance assays
- Systems biology researchers — integrate proteomics with transcriptomics and contextualize PTM findings
- Bioanalytical method developers — optimize LC-MS/MS protocols and troubleshoot validation failures
Best For
- Diagnosing unexpected protein fold-changes or quantification inconsistencies across replicates
- Designing hypothesis-driven troubleshooting experiments with minimal sample waste
- Contextualizing post-translational modification findings within structural and biochemical frameworks
- Optimizing data quality control thresholds (peptide FDR, intensity thresholds, normalization strategies)
- Evaluating competing mechanistic explanations for anomalous results (technical vs. biological)
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