Retrieve QTL colocalisation results of a variant
Source:R/qtlColocalisationVariantQuery.R
qtlColocalisationVariantQuery.Rd
The colocalisation analysis in Open Target Genetics is performed using the coloc method (Giambartolomei et al., 2014). Coloc is a Bayesian method which, for two traits, integrates evidence over all variants at a locus to evaluate the following hypotheses: - H0: No association with either trait - H1: Association with trait 1, not with trait 2 - H2: Association with trait 2, not with trait 1 - H3: Association with trait 1 and trait 2, two independent SNPs - H4: Association with trait 1 and trait 2, one shared SNP This analysis tests whether two independent associations at the same locus are consistent with having a shared causal variant. Colocalisation of two independent associations from two GWAS studies may suggest a shared causal mechanism.
Arguments
- study_id
Character: Study ID(s) generated by Open Targets Genetics (e.g GCST90002357).
- variant_id
Character: generated ID for variants by Open Targets Genetics (e.g. 1_154119580_C_A) or rsId (rs2494663).
Value
Returns a data frame of the colocalisation information for a lead variant in a specific study. The output is a tidy data frame with the following data structure:
qtlStudyName
: Character vector. QTL study name.phenotypeId
: Character vector. Phenotype ID.gene.id
: Character vector. Gene ID.gene.symbol
: Character vector. Gene symbol.name
: Character vector. Tissue name.indexVariant.id
: Character vector. Index variant ID.indexVariant.rsId
: Character vector. Index variant rsID.beta
: Numeric. Beta value.h4
: Numeric. h4 value.h3
: Numeric. h3 value.log2h4h3
: Numeric. Log2(h4/h3) value.