Introduction

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.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.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 .afournier@unimelb.edu.au.Supplementary data are available at Bioinformatics online.

Publications

  1. GWAlpha: genome-wide estimation of additive effects (alpha) based on trait quantile distribution from pool-sequencing experiments.
    Cite this
    Fournier-Level A, Robin C, Balding DJ, 2017-04-01 - Bioinformatics (Oxford, England)

Credits

  1. Alexandre Fournier-Level
    Developer

  2. Charles Robin
    Developer

  3. David J Balding
    Investigator

    School of Mathematics and Statistics, The University of Melbourne, Australia

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Summary
AccessionBT000228
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionAustralia
Submitted ByDavid J Balding