Proteomics Data Retrieval

COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

KEY PRINCIPLES

1. ProteomeXchange is the aggregator -- it indexes datasets from PRIDE, MassIVE, PeptideAtlas, jPOST, and iProX
2. MassIVE has richer metadata -- includes summaries, keywords, modifications, and contacts
3. Search both repositories -- ProteomeXchange for breadth, MassIVE for detail
4. Species uses NCBI taxonomy IDs -- human = 9606, mouse = 10090, rat = 10116
5. Accession formats: PXD (ProteomeXchange), MSV (MassIVE) -- both accepted by MassIVE_get_dataset
6. LOOK UP DON'T GUESS -- Never assume which datasets exist, their accessions, or their instrument types. Always search and retrieve metadata to confirm.

Domain Reasoning: Dataset Quality Assessment

Dataset quality depends on instrument, sample preparation, and quantification method. TMT/iTRAQ (isobaric labeling) datasets have ratio compression and co-isolation interference biases that differ from label-free quantification (LFQ). DIA datasets require different analysis pipelines than DDA. Check the original publication for methods before reusing data in a meta-analysis or cross-study comparison. Instrument resolution (Orbitrap > ion trap) and acquisition mode (DIA > DDA for completeness) directly affect how many proteins are quantified and at what confidence.

Core Repositories Integrated

Workflow Overview

Query (keyword / species / accession)
|
+-- PHASE 0: Input Resolution
|   Determine search type: keyword, species, or accession lookup
|
+-- PHASE 1: Repository Search
|   Search MassIVE and/or ProteomeXchange based on query type
|
+-- PHASE 2: Dataset Detail Retrieval
|   Get full metadata for promising hits
|
+-- PHASE 3: Result Synthesis
    Compile datasets with metadata, publications, and relevance assessment

Phase 0: Input Resolution

Objective: Determine the query type and prepare appropriate search parameters.

Decision Logic

• Accession provided (e.g., PXD000001, MSV000079514):
  • PXD accession: call ProteomeXchange_get_dataset and optionally MassIVE_get_dataset
  • MSV accession: call MassIVE_get_dataset
  • Skip Phase 1, go directly to Phase 2
• Species name provided (e.g., "human", "mouse"):
  • Map to NCBI taxonomy ID: human=9606, mouse=10090, rat=10116, yeast=559292, zebrafish=7955, fly=7227, worm=6239, arabidopsis=3702
  • Use MassIVE_search_datasets with species filter
• Keyword provided (e.g., "phosphoproteomics", "breast cancer"):
  • Use ProteomeXchange_search_datasets with query parameter
  • MassIVE does not support keyword search -- use ProteomeXchange for keyword queries

Phase 1: Repository Search

Objective: Find relevant datasets across repositories.

Tools

MassIVE_search_datasets:

• page_size: Number of results to return (integer, max 100, default 10)
• species: NCBI taxonomy ID string to filter by species (e.g., "9606" for human)
• Returns: Array of dataset objects with accessions (array), title, summary, species, instruments, keywords
• Note: No keyword/text search parameter -- filtering is by species only

ProteomeXchange_search_datasets:

• query: Optional search filter -- keyword or dataset accession (e.g., "phosphoproteomics", "PXD")
• limit: Max results (1-50, default 10)
• Returns: {data: [{accession, title, species}], metadata: {source, total_returned, query}}

Workflow

1. For species-specific search:

   • Call MassIVE_search_datasets(page_size=20, species="9606") for species-filtered results
   • Call ProteomeXchange_search_datasets(limit=20) for broader listing

2. For keyword search:

   • Call ProteomeXchange_search_datasets(query="keyword", limit=20)
   • Review titles for relevance

3. For comprehensive discovery:

   • Call both tools in parallel
   • Merge results, deduplicate by accession (PXD accessions may appear in both)

Response Format Notes

• MassIVE_search_datasets: Returns a direct array (no {data: ...} wrapper)
• ProteomeXchange_search_datasets: Returns {data: [...], metadata: {...}}

Phase 2: Dataset Detail Retrieval

Objective: Get full metadata for datasets of interest.

Tools

MassIVE_get_dataset:

• accession: Dataset accession -- accepts both MSV and PXD formats (e.g., "MSV000079514", "PXD003971")
• Returns: Object with accessions, title, summary, species, instruments, keywords, contacts, publications, modifications

ProteomeXchange_get_dataset:

• px_id: ProteomeXchange identifier in PXD format (e.g., "PXD000001")
• Returns: {data: {px_id, title, species, identifiers, instruments, publications, file_count}, metadata: {...}}

Workflow

1. For each promising dataset from Phase 1, call the appropriate detail tool
2. Extract key metadata: title, species, instruments, publications (PubMed/DOI), modifications
3. For PXD accessions: prefer ProteomeXchange_get_dataset for file count; use MassIVE_get_dataset for richer summary/keywords

Key Fields to Extract

• title: Dataset name/description
• species: Organism(s) studied
• instruments: Mass spectrometer(s) used (e.g., Orbitrap, Q Exactive, TripleTOF)
• publications: PubMed IDs and DOIs for associated papers
• modifications: PTMs studied (from MassIVE only)
• file_count: Number of raw files (from ProteomeXchange only)
• keywords: Topic tags (from MassIVE only)

Phase 3: Result Synthesis

Objective: Compile and present dataset results in a structured format.

Report Format

# Proteomics Dataset Search Results
**Query**: [original query]
**Date**: YYYY-MM-DD
**Repositories searched**: MassIVE, ProteomeXchange

## Summary
Found N datasets matching [criteria].

## Datasets

### 1. [Title]
- **Accession**: PXD/MSV number
- **Species**: [organism]
- **Instruments**: [MS platforms]
- **Publications**: [PubMed IDs / DOIs]
- **Modifications**: [PTMs if available]
- **Files**: [count if available]
- **Summary**: [brief description]

### 2. [Title]
...

## Data Gaps
[Note any limitations in search coverage]

Tool Parameter Reference

Response Format Notes:

• MassIVE_search_datasets: Returns direct array of dataset objects (no wrapper)
• MassIVE_get_dataset: Returns direct object (no wrapper)
• ProteomeXchange_search_datasets: Returns {data: [...], metadata: {...}}
• ProteomeXchange_get_dataset: Returns {data: {...}, metadata: {...}}

Fallback Strategies

Common Species Taxonomy IDs

Interpretation Framework

Interpreting dataset search results:

• Datasets with both MassIVE and ProteomeXchange accessions generally have richer metadata; MassIVE provides summaries and keywords while ProteomeXchange provides file counts -- cross-reference both for a complete picture.
• Instrument type determines data quality ceiling: high-resolution instruments (Orbitrap, timsTOF) produce higher mass accuracy and more reliable quantification than older ion trap platforms.
• A dataset lacking a peer-reviewed publication may still be valuable, but its experimental design and processing pipeline cannot be independently verified -- weight such datasets lower in meta-analyses.

Synthesis questions to address in the report:

1. Do multiple independent datasets for the same organism/condition show consistent protein identifications, or do discrepancies suggest batch effects?
2. Is the instrument platform appropriate for the analysis type (e.g., DIA requires high-resolution; TMT requires MS3 or calibrated MS2)?
3. Are the reported PTM types and species consistent with the user's research question, or is additional filtering needed?

Limitations

• MassIVE: No keyword/text search -- only species-based filtering via species parameter
• ProteomeXchange: Limited metadata in search results (no summaries or keywords); get details via Dataverse_get_dataset
• No full-text search: Cannot search within dataset descriptions or abstracts across repositories
• No download: These tools retrieve metadata only, not raw data files
• Rate limits: Both APIs may throttle under heavy load; keep page_size/limit reasonable
• Coverage: ProteomeXchange is the most comprehensive but may lag behind individual repositories for very recent submissions

Integration with Other Skills

References

• MassIVE: https://massive.ucsd.edu
• ProteomeXchange: http://www.proteomexchange.org
• PRIDE: https://www.ebi.ac.uk/pride
• ProXI API: https://github.com/PRIDE-Archive/proxi-schemas