Back to search

Article

A Unifying Statistical Framework to Discover Disease Genes from GWAS

2022-04-29

Abstract excerpt

<h4>ABSTRACT</h4> Genome-wide association studies (GWAS) identify genomic loci associated with complex traits, but it remains an open challenge to identify the genes underlying the association signals. Here, we extend the equations of statistical fine-mapping, to compute the probability that each gene in the human genome is targeted by a causal variant, given a particular trait. Our computations are enabled by se...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
32cc05a4-9f2f-5b52-b7af-4472f49bf9a5
DOI
10.1101/2022.04.28.489887
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A Unifying Statistical Framework to Discover Disease Genes from GWASDOI 10.1101/2022.04.28.489887
Select a neighboring publication to make it the new centre.