GWAlpha: genome-wide estimation of additive effects (alpha) based on trait quantile distribution from pool-sequencing experiments | Zendy

Alexandre FournierLevel | Zendy; Charles Robin | Zendy; David J. Balding | Zendy

Open Access

GWAlpha: genome-wide estimation of additive effects (alpha) based on trait quantile distribution from pool-sequencing experiments

Author(s) -

Alexandre FournierLevel,

Charles Robin,

David J. Balding

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw805

Subject(s) - quantile , trait , alpha (finance) , computational biology , statistics , estimation , biology , genetics , econometrics , computer science , evolutionary biology , mathematics , construct validity , management , economics , programming language , psychometrics

Sequencing pools of individuals (Pool-Seq) is a cost-effective way to gain insight into the genetics of complex traits, but as yet no parametric method has been developed to both test for genetic effects and estimate their magnitude. Here, we propose GWAlpha, a flexible method to obtain parametric estimates of genetic effects genome-wide from Pool-Seq experiments.

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