Document Type
Article
Publication Date
8-23-2021
Publication Title
Genome biology
Keywords
JMG
JAX Source
Genome Biol 2021 Aug 23; 22(1):241
Volume
22
Issue
1
First Page
241
Last Page
241
ISSN
1474-760X
PMID
34425882
DOI
https://doi.org/10.1186/s13059-021-02450-8
Abstract
Genome-wide association studies reveal many non-coding variants associated with complex traits. However, model organism studies largely remain as an untapped resource for unveiling the effector genes of non-coding variants. We develop INFIMA, Integrative Fine-Mapping, to pinpoint causal SNPs for diversity outbred (DO) mice eQTL by integrating founder mice multi-omics data including ATAC-seq, RNA-seq, footprinting, and in silico mutation analysis. We demonstrate INFIMA's superior performance compared to alternatives with human and mouse chromatin conformation capture datasets. We apply INFIMA to identify novel effector genes for GWAS variants associated with diabetes. The results of the application are available at http://www.statlab.wisc.edu/shiny/INFIMA/ .
Recommended Citation
Dong C,
Simonett S,
Shin S,
Stapleton D,
Schueler K,
Churchill G,
Lu L,
Liu X,
Jin F,
Li Y,
Attie A,
Keller M,
Keleş S.
INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants. Genome Biol 2021 Aug 23; 22(1):241
Comments
This article is licensed under a Creative Commons Attribution 4.0 International License.