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INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants
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INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants
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Journal Article
INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants
2021
Overview
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,
In
tegrative
Fi
ne-
Ma
pping, 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/
.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
/ Animals
/ ATAC-seq
/ Biomedical and Life Sciences
/ Chromatin Immunoprecipitation Sequencing
/ Diabetes
/ Genetic Predisposition to Disease
/ genome
/ Genome-wide association studies
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Humans
/ Method
/ Mice
/ Microbial Genetics and Genomics
/ Molecular quantitative trait loci
/ Polymorphism, Single Nucleotide - genetics
/ Quantitative Trait Loci - genetics
/ RNA-Seq
/ Sexes
