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

Fournier-Level, A; Robin, C; Balding, DJ; (2016) GWAlpha: genome-wide estimation of additive effects (alpha) based on trait quantile distribution from pool-sequencing experiments. Bioinformatics , 33 (8) pp. 1246-1247. 10.1093/bioinformatics/btw805. Green open access

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Abstract

MOTIVATION: 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. RESULTS: We showed that GWAlpha powerfully replicates the results of Genome-Wide Association Studies (GWAS) from model organisms. We perform simulation studies that illustrate the effect on power of sample size and number of pools and test the method on different experimental data. AVAILABILITY AND IMPLEMENTATION: GWAlpha is implemented in python, designed to run on Linux operating system and tested on Mac OS. It is freely available at https://github.com/aflevel/GWAlpha CONTACT: afournier@unimelb.edu.auSupplementary information: Supplementary data are available at Bioinformatics online.

Type: Article
Title: GWAlpha: genome-wide estimation of additive effects (alpha) based on trait quantile distribution from pool-sequencing experiments
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/bioinformatics/btw805
Publisher version: http://doi.org/10.1093/bioinformatics/btw805
Language: English
Additional information: © The Author 2016. Published by Oxford University Press. All rights reserved. This is a pre-copyedited, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The version of record Fournier-Level, A; Robin, C; Balding, DJ; (2016) GWAlpha: genome-wide estimation of additive effects (alpha) based on trait quantile distribution from pool-sequencing experiments. Bioinformatics 10.1093/bioinformatics/btw805 is available online at: http://doi.org/10.1093/bioinformatics/btw805
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI: http://discovery.ucl.ac.uk/id/eprint/1534347
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