ArticleGenome biology2021
INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants.
Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Multi-tissue multi-omics integration reveals tissue-specific pathways, gene networks and drug candidates for type 1 diabetes.Diabetologia · 2026Article
- Distinct genetic architecture of gene and isoform level QTL in the Diversity Outbred (DO) mouse population.bioRxiv : the preprint server for biology · 2026Article
- Stimulation to secrete insulin induces pancreatic β-cell dysfunction through Tfe3 activation.iScience · 2026Article
- Multiple promoter and enhancer differences likely contribute to augmented G6PC2 expression in human versus mouse pancreatic islet alpha cells.Journal of molecular endocrinology · 2024Article
- Article
- AdaLiftOver: high-resolution identification of orthologous regulatory elements with Adaptive liftOver.Bioinformatics (Oxford, England) · 2023Article
- Analysis of a genetic region affecting mouse body weight.Physiological genomics · 2023Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
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/ .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.