tooluniverse-regulatory-variant-analysis

Build evidence across four questions: whether the variant overlaps a regulatory element (RegulomeDB, ENCODE), whether it disrupts a TF binding site, whether eQTL data links it to a gene (GTEx), and whether GWAS shows trait association. Converging evidence across multiple lines indicates high-confidence regulatory impact.

Use GTEx_query_eqtl with a gene symbol or Ensembl ID to get tissue-specific SNP-gene associations with normalized effect sizes and p-values. Confirm the gene is actually expressed in the relevant tissue with GTEx_get_median_gene_expression before weighting the eQTL evidence.

RegulomeDB scores in categories 1a-2a indicate strong regulatory evidence such as eQTL overlap plus TF binding and chromatin accessibility. Scores 3a-6 represent progressively weaker evidence, and the scores are heuristic rather than proof of functional impact.

Free-text trait matching in the GWAS Catalog is imprecise because it uses controlled vocabulary. Resolve the trait name to an EFO ID with ols_search_terms first, then query with the efo_id parameter, or broaden the trait term.

Use regulatory variant analysis for non-coding variants such as intronic, UTR, and intergenic SNPs where the question is regulatory mechanism, eQTL effects, or GWAS hit annotation. Coding variant pathogenicity and ACMG clinical classification require a dedicated coding-variant interpretation skill.

eQTL analysis identifies correlation, not causation, so fine-mapping is needed to pinpoint causal variants. GTEx data is from v8 and some v10 endpoints return empty, and GWAS associations are population-level, so individual effects depend on genetic background.