Genome Biology, 2021-08, Vol.22 (1), p.241-32, Article 241
2021
Volltextzugriff (PDF)
Details
- Autor(en) / Beteiligte
- Titel
- INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants
- Ist Teil von
- Genome Biology, 2021-08, Vol.22 (1), p.241-32, Article 241
- Ort / Verlag
- England: BioMed Central
- Erscheinungsjahr
- 2021
- Quelle
- MEDLINE
- Beschreibungen/Notizen
- 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/ .
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1474-760X, 1474-7596eISSN: 1474-760XDOI: 10.1186/s13059-021-02450-8Titel-ID: cdi_doaj_primary_oai_doaj_org_article_47ca5af6b89a420aa3de1a894239c486
- Format
- –
- Schlagworte
- Animals, ATAC-seq, Base Sequence, Chromatin, Chromatin - metabolism, Chromatin Immunoprecipitation Sequencing, Computer Simulation, Conformation, Diabetes, Diabetes mellitus, Diversity outbred mouse, Fine-mapping, Footprinting, Gene expression, Gene mapping, Genetic Predisposition to Disease, Genetic Variation, Genome-wide association studies, Genome-Wide Association Study, Genomes, Genomics, Humans, Method, Mice, Mitochondrial DNA, Molecular quantitative trait loci, Pancreatic islets, Physical Chromosome Mapping, Polymorphism, Single Nucleotide - genetics, Quantitative Trait Loci - genetics, RNA-Seq, Sexes, Single-nucleotide polymorphism, Statistics as Topic, Transcriptome - genetics