Gtex V2 Tools

Configuration File: gtex_v2_tools.json Tool Type: Local Tools Count: 14

This page contains all tools defined in the gtex_v2_tools.json configuration file.

Available Tools

GTEx_calculate_eqtl (Type: GTExV2Tool)

Calculate custom eQTL for any gene-variant pair in any tissue. Dynamically calculates gene-varian…

GTEx_calculate_eqtl tool specification

Tool Information:

  • Name: GTEx_calculate_eqtl

  • Type: GTExV2Tool

  • Description: Calculate custom eQTL for any gene-variant pair in any tissue. Dynamically calculates gene-variant association statistics including p-value, normalized effect size (NES), t-statistic, and genotype data. Works for both significant and non-significant associations. Returns detailed statistics even if association not in precomputed results. Use for: testing specific hypotheses, custom variant-gene pairs, dynamic eQTL analysis, validating findings. Requires all three: gencode_id, variant_id, and tissue_site_detail_id.

Parameters:

  • operation (string) (optional) Operation type

  • gencode_id (string) (required) Required: Versioned GENCODE ID (e.g. ENSG00000141510.18)

  • variant_id (string) (required) Required: GTEx variant ID

  • tissue_site_detail_id (string) (required) Required: Tissue ID (e.g. ‘Whole_Blood’)

  • dataset_id (string) (optional) No description

Example Usage:

query = {
    "name": "GTEx_calculate_eqtl",
    "arguments": {
        "gencode_id": "example_value",
        "variant_id": "example_value",
        "tissue_site_detail_id": "example_value"
    }
}
result = tu.run(query)

GTEx_get_dataset_info (Type: GTExV2Tool)

Get GTEx dataset metadata and version information. Returns dataset details including GENCODE vers…

GTEx_get_dataset_info tool specification

Tool Information:

  • Name: GTEx_get_dataset_info

  • Type: GTExV2Tool

  • Description: Get GTEx dataset metadata and version information. Returns dataset details including GENCODE version, genome build (GRCh38/hg38), dbSNP build, sample counts, tissue counts, and release information. Shows Adult GTEx V11 details (January 2026) by default. Use for: understanding data versions, checking sample sizes, verifying genome builds, documentation. Check this first to understand what data is available.

Parameters:

  • operation (string) (optional) Operation type

  • dataset_id (string) (optional) Optional: Specific dataset ID. Omit to get all datasets

Example Usage:

query = {
    "name": "GTEx_get_dataset_info",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_eqtl_genes (Type: GTExV2Tool)

Get eQTL genes (eGenes) with significant cis-eQTLs. Returns genes with at least one significant e…

GTEx_get_eqtl_genes tool specification

Tool Information:

  • Name: GTEx_get_eqtl_genes

  • Type: GTExV2Tool

  • Description: Get eQTL genes (eGenes) with significant cis-eQTLs. Returns genes with at least one significant expression quantitative trait locus (eQTL) in specified tissues. Includes allelic fold change, p-values, q-values (FDR < 0.05), and effect sizes. Filter by tissue or get all eGenes. Use for: identifying genes with genetic regulation, finding tissue-specific eQTLs, studying regulatory variants, genetic association studies. Essential for understanding genetic control of gene expression.

Parameters:

  • operation (string) (optional) Operation type

  • tissue_site_detail_id (array) (optional) Optional: Filter by tissue IDs. Omit for all tissues

  • dataset_id (string) (optional) GTEx dataset version

  • page (integer) (optional) No description

  • items_per_page (integer) (optional) No description

Example Usage:

query = {
    "name": "GTEx_get_eqtl_genes",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_finemapping_and_independent_eqtl (Type: GTExV2Tool)

Get GTEx statistical fine-mapping credible sets and conditionally-independent eQTLs - identifying…

GTEx_get_finemapping_and_independent_eqtl tool specification

Tool Information:

  • Name: GTEx_get_finemapping_and_independent_eqtl

  • Type: GTExV2Tool

  • Description: Get GTEx statistical fine-mapping credible sets and conditionally-independent eQTLs - identifying likely causal variants and multiple independent regulatory signals per gene beyond the marginal single-tissue eQTL list. result_type=’finemapping’ (default) returns DAP-G credible sets with per-variant PIP (posterior inclusion probability) and setId. result_type=’independent’ returns rank-ordered conditionally-independent (secondary) eQTL signals. Based on gtex_v8. Example: ERAP2 (ENSG00000164308.16) Adipose_Subcutaneous -> method DAP-G, variant chr5_96916728_G_A_b38, pip 0.9468, setId 1; independent -> rs2927608 rank 1 pValue 2.88e-123 nes 1.076.

Parameters:

  • operation (string) (optional) Operation type

  • result_type (string) (optional) ‘finemapping’ for DAP-G credible sets with PIP (default), ‘independent’ for rank-ordered conditionally-independent eQTL signals.

  • gencode_id ([‘string’, ‘array’]) (optional) Gene identifier: gene symbol (e.g. ‘ERAP2’), Ensembl ID, or versioned GENCODE ID (e.g. ‘ENSG00000164308.16’). Auto-resolved.

  • gene_symbol (string) (optional) Gene symbol alias for gencode_id.

  • tissue_site_detail_id (array) (optional) Optional tissue ID(s) to filter (e.g. [‘Adipose_Subcutaneous’]). Omit for all tissues.

  • page (integer) (optional) Page number (0-based)

  • items_per_page (integer) (optional) Results per page

  • dataset_id (string) (optional) GTEx dataset version (default gtex_v8)

Example Usage:

query = {
    "name": "GTEx_get_finemapping_and_independent_eqtl",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_gene_expression (Type: GTExV2Tool)

Get gene expression data at individual sample level (not aggregated). Returns normalized expressi…

GTEx_get_gene_expression tool specification

Tool Information:

  • Name: GTEx_get_gene_expression

  • Type: GTExV2Tool

  • Description: Get gene expression data at individual sample level (not aggregated). Returns normalized expression values (TPM) for each sample, allowing detailed distribution analysis. Can subset by donor attributes (sex, age_bracket) for demographic-specific analysis. Much more data than median expression. Use for: expression variability analysis, outlier detection, sample-level QC, demographic comparisons. Warning: large result sets for multiple genes/tissues.

Parameters:

  • operation (string) (optional) Operation type

  • gencode_id ([‘string’, ‘array’]) (required) Required: Versioned GENCODE ID(s)

  • tissue_site_detail_id (array) (optional) Optional: Filter by tissues

  • attribute_subset (string) (optional) Optional: Subset by donor sex or age bracket

  • dataset_id (string) (optional) No description

  • page (integer) (optional) No description

  • items_per_page (integer) (optional) No description

Example Usage:

query = {
    "name": "GTEx_get_gene_expression",
    "arguments": {
        "gencode_id": "example_value"
    }
}
result = tu.run(query)

GTEx_get_median_gene_expression (Type: GTExV2Tool)

Get median gene expression levels across GTEx tissues. Returns median expression in TPM (Transcri…

GTEx_get_median_gene_expression tool specification

Tool Information:

  • Name: GTEx_get_median_gene_expression

  • Type: GTExV2Tool

  • Description: Get median gene expression levels across GTEx tissues. Returns median expression in TPM (Transcripts Per Million) for one or more genes across 54 tissue sites. Filter by specific tissues or get expression across all tissues. Based on Adult GTEx V11 (January 2026). Use for: tissue-specific expression profiling, identifying highly expressed genes, comparing expression patterns across tissues. Example: Get brain vs liver expression for TP53 gene.

Parameters:

  • operation (string) (optional) Operation type

  • gencode_id ([‘string’, ‘array’]) (optional) Gene identifier(s): gene symbol (e.g. ‘TP53’), unversioned Ensembl ID (e.g. ‘ENSG00000141510’), or versioned GENCODE ID (e.g. ‘ENSG00000141510.18’). Auto-resolved to versioned GENCODE ID. Can be single string or array.

  • tissue_site_detail_id (array) (optional) Optional: Tissue IDs to filter (e.g. [‘Liver’, ‘Brain_Cortex’]). Omit for all tissues. See GTEx_get_tissue_sites for valid IDs

  • dataset_id (string) (optional) GTEx dataset version (default: gtex_v8; v10 returns empty for most endpoints)

  • page (integer) (optional) Page number for pagination (0-based)

  • items_per_page (integer) (optional) Results per page

  • gene_symbol (string) (optional) Gene symbol alias for gencode_id (e.g., “TP53”, “COL5A1”)

Example Usage:

query = {
    "name": "GTEx_get_median_gene_expression",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_median_transcript_expression (Type: GTExV2Tool)

Get GTEx transcript/isoform-level median expression: per-transcript (ENST) median TPM across tiss…

GTEx_get_median_transcript_expression tool specification

Tool Information:

  • Name: GTEx_get_median_transcript_expression

  • Type: GTExV2Tool

  • Description: Get GTEx transcript/isoform-level median expression: per-transcript (ENST) median TPM across tissues, enabling isoform-usage and transcript-switching analysis that gene-level expression cannot reveal. Based on gtex_v8. Example: BRCA1 (ENSG00000012048.20) in Whole_Blood -> transcript ENST00000352993.7 median 0.37 TPM, ENST00000354071.7 median 0.0, ENST00000357654.7 median 0.07.

Parameters:

  • operation (string) (optional) Operation type

  • gencode_id ([‘string’, ‘array’]) (optional) Gene identifier(s): gene symbol (e.g. ‘BRCA1’), Ensembl ID, or versioned GENCODE ID (e.g. ‘ENSG00000012048.20’). Auto-resolved.

  • gene_symbol (string) (optional) Gene symbol alias for gencode_id.

  • tissue_site_detail_id (array) (optional) Optional tissue ID(s) to filter (e.g. [‘Whole_Blood’]). Omit for all tissues. See GTEx_get_tissue_sites.

  • page (integer) (optional) Page number (0-based)

  • items_per_page (integer) (optional) Results per page

  • dataset_id (string) (optional) GTEx dataset version (default gtex_v8)

Example Usage:

query = {
    "name": "GTEx_get_median_transcript_expression",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_multi_tissue_eqtls (Type: GTExV2Tool)

Get multi-tissue eQTL meta-analysis results (Metasoft). Returns m-values (posterior probability o…

GTEx_get_multi_tissue_eqtls tool specification

Tool Information:

  • Name: GTEx_get_multi_tissue_eqtls

  • Type: GTExV2Tool

  • Description: Get multi-tissue eQTL meta-analysis results (Metasoft). Returns m-values (posterior probability of eQTL effect in each tissue), normalized effect sizes, p-values, and standard errors across all tissues for a gene-variant pair. Shows tissue-sharing patterns of eQTL effects. Use for: understanding tissue-specificity of eQTLs, finding shared vs tissue-specific effects, cross-tissue meta-analysis, regulatory mechanism studies. Requires gencode_id, optionally filter by variant_id.

Parameters:

  • operation (string) (optional) Operation type

  • gencode_id (string) (required) Required: Versioned GENCODE ID

  • variant_id (string) (optional) Optional: GTEx variant ID to filter specific variant

  • dataset_id (string) (optional) No description

  • page (integer) (optional) No description

  • items_per_page (integer) (optional) No description

Example Usage:

query = {
    "name": "GTEx_get_multi_tissue_eqtls",
    "arguments": {
        "gencode_id": "example_value"
    }
}
result = tu.run(query)

GTEx_get_sample_info (Type: GTExV2Tool)

Get detailed GTEx sample and subject metadata. Returns sample IDs, tissue types, donor demographi…

GTEx_get_sample_info tool specification

Tool Information:

  • Name: GTEx_get_sample_info

  • Type: GTExV2Tool

  • Description: Get detailed GTEx sample and subject metadata. Returns sample IDs, tissue types, donor demographics (age, sex), ischemic time, RIN scores, Hardy scale, pathology notes, and QC metrics. Filter by sample ID, subject ID, tissue, demographics, or data type. Use for: sample selection, cohort design, QC filtering, demographic analysis, understanding data provenance. Essential for selecting appropriate samples for analysis.

Parameters:

  • operation (string) (optional) Operation type

  • sample_id (array) (optional) Optional: GTEx sample IDs

  • subject_id (array) (optional) Optional: GTEx subject/donor IDs

  • tissue_site_detail_id (array) (optional) Optional: Filter by tissues

  • sex (string) (optional) Optional: Filter by donor sex

  • age_bracket (array) (optional) Optional: Filter by age brackets

  • dataset_id (string) (optional) No description

  • page (integer) (optional) No description

  • items_per_page (integer) (optional) No description

Example Usage:

query = {
    "name": "GTEx_get_sample_info",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_single_nucleus_expression (Type: GTExV2Tool)

Get GTEx single-nucleus (snRNA-seq) gene expression resolved by cell type from the snRNA-seq pilo…

GTEx_get_single_nucleus_expression tool specification

Tool Information:

  • Name: GTEx_get_single_nucleus_expression

  • Type: GTExV2Tool

  • Description: Get GTEx single-nucleus (snRNA-seq) gene expression resolved by cell type from the snRNA-seq pilot dataset (bulk-tissue GTEx cannot resolve cell types). result_type=’detail’ (default) returns per-cell-type mean/median (with and without zeros), cell counts, and number of zeros for a gene. result_type=’summary’ returns a tissue x cell-type cell-count summary (numCells per cell type). Uses datasetId gtex_snrnaseq_pilot. Example: BRCA1 (ENSG00000012048.20) Muscle_Skeletal -> Myocyte (NMJ-rich) count 6 meanWithoutZeros 1.455; Endothelial cell (vascular) count 38 meanWithoutZeros 2.264.

Parameters:

  • operation (string) (optional) Operation type

  • result_type (string) (optional) ‘detail’ for per-cell-type expression stats (default), ‘summary’ for tissue x cell-type cell-count summary.

  • gencode_id ([‘string’, ‘array’]) (optional) Gene identifier(s): gene symbol (e.g. ‘BRCA1’), Ensembl ID, or versioned GENCODE ID (e.g. ‘ENSG00000012048.20’). Auto-resolved.

  • gene_symbol (string) (optional) Gene symbol alias for gencode_id.

  • tissue_site_detail_id (array) (optional) Optional tissue ID(s) (e.g. [‘Muscle_Skeletal’]). Omit for all snRNA-seq tissues.

  • dataset_id (string) (optional) GTEx dataset version (default gtex_snrnaseq_pilot; snRNA-seq data only exists in the pilot dataset).

  • page (integer) (optional) Page number (0-based)

  • items_per_page (integer) (optional) Results per page

Example Usage:

query = {
    "name": "GTEx_get_single_nucleus_expression",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_single_tissue_eqtls (Type: GTExV2Tool)

Get significant single-tissue eQTL associations. Returns precomputed gene-variant associations wi…

GTEx_get_single_tissue_eqtls tool specification

Tool Information:

  • Name: GTEx_get_single_tissue_eqtls

  • Type: GTExV2Tool

  • Description: Get significant single-tissue eQTL associations. Returns precomputed gene-variant associations with p-values, effect sizes (NES), and genomic positions. Query by gene ID, variant ID, tissue, or combination. Results show which genetic variants affect gene expression in specific tissues. Use for: finding eQTLs for candidate genes, looking up variant effects, tissue-specific regulatory analysis, GWAS follow-up. Must provide at least one filter: gencode_id, variant_id, or tissue_site_detail_id.

Parameters:

  • operation (string) (optional) Operation type

  • gencode_id (array) (optional) Optional: Versioned GENCODE ID(s) to query

  • variant_id (array) (optional) Optional: GTEx variant ID(s) to query

  • tissue_site_detail_id (array) (optional) Optional: Tissue ID(s) to filter. At least one of gencode_id, variant_id, or tissue_site_detail_id required

  • dataset_id (string) (optional) No description

  • page (integer) (optional) No description

  • items_per_page (integer) (optional) No description

Example Usage:

query = {
    "name": "GTEx_get_single_tissue_eqtls",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_single_tissue_sqtls (Type: GTExV2Tool)

Get GTEx single-tissue splicing QTLs (sQTLs) and sGenes - a molecular layer distinct from eQTLs t…

GTEx_get_single_tissue_sqtls tool specification

Tool Information:

  • Name: GTEx_get_single_tissue_sqtls

  • Type: GTExV2Tool

  • Description: Get GTEx single-tissue splicing QTLs (sQTLs) and sGenes - a molecular layer distinct from eQTLs that captures genetic regulation of alternative splicing. result_type=’sqtl’ (default) returns significant single-tissue sQTL associations for a gene/tissue (variant, pValue, nes, and phenotypeId which encodes the LeafCutter intron-excision cluster, e.g. chr5:96900189:96901506:clu_31758). result_type=’sgene’ returns genes with at least one significant sQTL in a tissue, with qValue. Based on gtex_v8. Example: ERAP2 (ENSG00000164308.16) in Whole_Blood -> rs72772072 / chr5_96659855_A_G_b38, pValue 1.2e-06, nes 0.439.

Parameters:

  • operation (string) (optional) Operation type

  • result_type (string) (optional) ‘sqtl’ for single-tissue sQTL associations (default), ‘sgene’ for genes with significant sQTLs in a tissue.

  • gencode_id ([‘string’, ‘array’]) (optional) Gene identifier(s) for sqtl mode: gene symbol (e.g. ‘ERAP2’), Ensembl ID, or versioned GENCODE ID (e.g. ‘ENSG00000164308.16’). Auto-resolved.

  • gene_symbol (string) (optional) Gene symbol alias for gencode_id.

  • variant_id ([‘string’, ‘array’]) (optional) Optional GTEx variant ID(s) to filter sqtl results (e.g. ‘chr5_96659855_A_G_b38’).

  • tissue_site_detail_id (array) (optional) Tissue ID(s) (e.g. [‘Whole_Blood’]). Recommended for both modes. See GTEx_get_tissue_sites.

  • page (integer) (optional) Page number (0-based)

  • items_per_page (integer) (optional) Results per page

  • dataset_id (string) (optional) GTEx dataset version (default gtex_v8)

Example Usage:

query = {
    "name": "GTEx_get_single_tissue_sqtls",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_tissue_sites (Type: GTExV2Tool)

Get all available GTEx tissue sites with metadata. Returns tissue IDs, names, sample counts, eGen…

GTEx_get_tissue_sites tool specification

Tool Information:

  • Name: GTEx_get_tissue_sites

  • Type: GTExV2Tool

  • Description: Get all available GTEx tissue sites with metadata. Returns tissue IDs, names, sample counts, eGene counts, and color codes for 54 non-diseased tissue sites. Includes RNA-seq sample summaries with donor age and sex statistics. Use for: discovering available tissues, finding tissue IDs for queries, checking sample sizes, understanding tissue coverage. Essential first step before querying tissue-specific data.

Parameters:

  • operation (string) (optional) Operation type

  • dataset_id (string) (optional) GTEx dataset version

  • page (integer) (optional) Page number

  • items_per_page (integer) (optional) Results per page

Example Usage:

query = {
    "name": "GTEx_get_tissue_sites",
    "arguments": {
    }
}
result = tu.run(query)

GTEx_get_top_expressed_genes (Type: GTExV2Tool)

Get top expressed genes in a specific tissue sorted by median expression. Returns gene list with …

GTEx_get_top_expressed_genes tool specification

Tool Information:

  • Name: GTEx_get_top_expressed_genes

  • Type: GTExV2Tool

  • Description: Get top expressed genes in a specific tissue sorted by median expression. Returns gene list with expression levels (TPM), useful for understanding tissue-specific gene signatures. Option to filter mitochondrial genes (default: true). Use for: tissue characterization, finding housekeeping genes, identifying tissue markers, quality control. Essential for understanding what genes are active in each tissue type.

Parameters:

  • operation (string) (optional) Operation type

  • tissue_site_detail_id (string) (required) Required: Tissue ID (e.g. ‘Liver’, ‘Brain_Cortex’). Use GTEx_get_tissue_sites to find valid IDs

  • filter_mt_genes (boolean) (optional) Exclude mitochondrial genes from results

  • dataset_id (string) (optional) No description

  • page (integer) (optional) No description

  • items_per_page (integer) (optional) No description

Example Usage:

query = {
    "name": "GTEx_get_top_expressed_genes",
    "arguments": {
        "tissue_site_detail_id": "example_value"
    }
}
result = tu.run(query)