INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants.

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Title: INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants.
Authors: Dong C; Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA., Simonett SP; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA., Shin S; Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX, USA., Stapleton DS; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA., Schueler KL; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA., Churchill GA; The Jackson Laboratory, Bar Harbor, ME, USA., Lu L; Case Western University, Cleveland, OH, USA., Liu X; Case Western University, Cleveland, OH, USA., Jin F; Case Western University, Cleveland, OH, USA., Li Y; Case Western University, Cleveland, OH, USA., Attie AD; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA., Keller MP; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA. mark.keller@wisc.edu., Keleş S; Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA. keles@stat.wisc.edu.; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA. keles@stat.wisc.edu.
Source: Genome biology [Genome Biol] 2021 Aug 23; Vol. 22 (1), pp. 241. Date of Electronic Publication: 2021 Aug 23.
Publication Type: Journal Article; Research Support, N.I.H., Extramural
Journal Info: Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1474-760X
DOI:10.1186/s13059-021-02450-8