EpiGEN: an epistasis simulation pipeline | Zendy

David B. Blumenthal | Zendy; Lorenzo Viola | Zendy; Markus List | Zendy; Jan Baumbach | Zendy; Paolo Tieri | Zendy; Tim Kacprowski | Zendy

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EpiGEN: an epistasis simulation pipeline

Author(s) -

David B. Blumenthal,

Lorenzo Viola,

Markus List,

Jan Baumbach,

Paolo Tieri,

Tim Kacprowski

Publication year - 2020

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa245

Subject(s) - epistasis , linkage disequilibrium , categorical variable , computer science , python (programming language) , software , pipeline (software) , single nucleotide polymorphism , data mining , linkage (software) , computational biology , machine learning , biology , genetics , programming language , genotype , gene

Simulated data are crucial for evaluating epistasis detection tools in genome-wide association studies. Existing simulators are limited, as they do not account for linkage disequilibrium (LD), support limited interaction models of single nucleotide polymorphisms (SNPs) and only dichotomous phenotypes or depend on proprietary software. In contrast, EpiGEN supports SNP interactions of arbitrary order, produces realistic LD patterns and generates both categorical and quantitative phenotypes.

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