Retrieve gene expression and omics datasets from ArrayExpress and BioStudies with gene disambiguation and quality assessment. Use for finding RNA-seq/microarray datasets by organism/tissue/condition, comparing across studies (case-control, time-series, dose-response), and assessing dataset suitability before downloading. Always uses English search terms.
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Retrieve gene expression experiments and multi-omics datasets with disambiguation and quality assessment.
IMPORTANT: Always use English terms in tool calls. Respond in the user's language.
LOOK UP DON'T GUESS: Never assume which datasets exist or their accessions. Always search to confirm.
Before retrieving, determine: organism, tissue, experimental design (case-control/time-series/dose-response). These affect which database to search and how to interpret results. RNA-seq provides wider dynamic range; microarray has extensive legacy data. Prioritize experiments with >=3 biological replicates, complete annotations, and both raw+processed data.
Phase 0: Clarify (if ambiguous) → Phase 1: Disambiguate → Phase 2: Search & Retrieve → Phase 3: ReportAsk ONLY if: gene name ambiguous, tissue/condition unclear, organism not specified. Skip for: specific accessions (E-MTAB-, E-GEOD-, S-BSST*), clear disease/tissue+organism, explicit platform requests.
Resolve official gene symbol (HGNC for human, MGI for mouse). Note common aliases for search expansion.
| User Query Type | Search Strategy |
|---|---|
| Specific accession | Direct retrieval |
| Gene + condition | "[gene] [condition]" + species filter |
| Disease only | "[disease]" + species filter |
| Technology-specific | Add platform keywords |
Search silently. Do NOT narrate the process.
# ArrayExpress search
result = tu.tools.arrayexpress_search_experiments(keywords="[gene/disease]", species="[species]", limit=20)
# Get experiment details, samples, files
details = tu.tools.arrayexpress_get_experiment(experiment_id=accession)
samples = tu.tools.arrayexpress_get_experiment_samples(experiment_id=accession)
files = tu.tools.arrayexpress_get_experiment_files(experiment_id=accession)
# BioStudies for multi-omics
biostudies = tu.tools.biostudies_search(query="[keywords]", pageSize=10)
study = tu.tools.biostudies_get_study(accession=study_accession)
study_files = tu.tools.biostudies_get_study_files(accession=study_accession)| Primary | Fallback |
|---|---|
| ArrayExpress search | BioStudies search |
| arrayexpress_get_experiment | biostudies_get_study |
| arrayexpress_get_experiment_files | Note "Files unavailable" |
Present as a Dataset Search Report. Hide search process. Include:
| Tier | Symbol | Criteria |
|---|---|---|
| High | ●●● | >=3 bio replicates, complete metadata, processed data available |
| Medium | ●●○ | 2-3 replicates OR some metadata gaps |
| Low | ●○○ | No replicates, sparse metadata, or access issues |
| Caution | ○○○ | Single sample, no replication, outdated platform |
Dataset quality: Prioritize >=3 biological replicates, complete annotations, both raw+processed data. Single-replicate experiments can inform but not be sole evidence.
Platform comparison: RNA-seq = wider dynamic range, novel transcripts. Microarray = probe-limited but extensive legacy data. Cross-platform combining requires batch correction.
Metadata scoring: Rate 0-5 on: (1) sample annotations, (2) design documented, (3) pipeline described, (4) raw data deposited, (5) publication linked. Score <=2 warrants caution.
GEO vs ArrayExpress: GEO has broader coverage (older studies); ArrayExpress enforces stricter metadata. BioStudies captures multi-omics. Search both.
| Error | Response |
|---|---|
| "No experiments found" | Broaden keywords, remove species filter, try synonyms |
| "Accession not found" | Verify format, check if withdrawn |
| "Files not available" | Note: "Data files restricted by submitter" |
| "API timeout" | Retry once, note "(metadata retrieval incomplete)" |
ArrayExpress: arrayexpress_search_experiments (search), arrayexpress_get_experiment (metadata), arrayexpress_get_experiment_files (downloads), arrayexpress_get_experiment_samples (annotations)
BioStudies: biostudies_search (search), biostudies_get_study (metadata+sections), biostudies_get_study_files (files)
Additional Sources:
GEO_search_rnaseq_datasets / geo_search_datasets -- GEO (largest RNA-seq repo)OmicsDI_search_datasets -- cross-repository aggregation (GEO+ArrayExpress+PRIDE+MassIVE)GTEx_get_expression_summary -- baseline tissue expression (54 normal tissues, param: gene_symbol)ENAPortal_search_studies -- sequencing studies (param: query with description="...")CxGDisc_search_datasets -- single-cell datasets (needs exact disease ontology terms)GxA_list_experiments / GxA_get_experiment_info / GxA_get_experiment_expression -- EBI Gene Expression Atlas: curated baseline (tissue) and differential (condition-comparison) bulk RNA-seq/microarray experiments. Filter GxA_list_experiments by species and experiment_type ("baseline" vs "differential") first; GxA_get_experiment_expression needs a specific experiment_accession (e.g. E-MTAB-2836) plus gene_id.ARCHS4_get_gene_expression / ARCHS4_get_gene_correlations -- ARCHS4: box-plot expression statistics (min/Q1/median/Q3/max, log2) across human/mouse tissues and cell lines, and top co-expressed genes by Pearson correlation across 300K+ uniformly reprocessed RNA-seq samples. Good for a quick baseline-expression sanity check or finding candidate co-regulated genes without running a full differential-expression pipeline.Bgee_search_genes / Bgee_get_gene_expression / Bgee_list_species -- Bgee: curated baseline expression-by-tissue calls across 29+ animal species (vs. ARCHS4's human/mouse-only reprocessed RNA-seq, or GxA's curated-but-narrower experiment set). Bgee_get_gene_expression needs BOTH an Ensembl gene ID and an NCBI taxonomy ID (e.g. gene_id="ENSG00000141510", species_id="9606" for human TP53) -- resolve the gene ID with Bgee_search_genes first if you only have a symbol. Use Bgee_list_species to confirm a species is covered before assuming Bgee has it. Best for cross-species comparison questions ("is gene X expressed in the same tissues in mouse and zebrafish?"), not for finding raw sequencing datasets to download.PubMed_search_articles -- dataset discovery via publicationsArrayExpress: keywords (free text), species (scientific name), array (platform filter), limit
BioStudies: query (free text), limit
mims-harvard/ToolUniverse
37bb81a
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