SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data

Effective population size (Ne ) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating Ne has been subject to much research over the last 80 years. Methods to estimate Ne from linkage disequilibrium (LD) were developed ~40 years ago but depend on...

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Published inFrontiers in genetics Vol. 6; p. 109
Main Authors Barbato, Mario, Orozco-terWengel, Pablo, Tapio, Miika, Bruford, Michael W.
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 20.03.2015
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ISSN1664-8021
1664-8021
DOI10.3389/fgene.2015.00109

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Summary:Effective population size (Ne ) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating Ne has been subject to much research over the last 80 years. Methods to estimate Ne from linkage disequilibrium (LD) were developed ~40 years ago but depend on the availability of large amounts of genetic marker data that only the most recent advances in DNA technology have made available. Here we introduce SNeP, a multithreaded tool to perform the estimate of Ne using LD using the standard PLINK input file format (.ped and.map files) or by using LD values calculated using other software. Through SNeP the user can apply several corrections to take account of sample size, mutation, phasing, and recombination rate. Each variable involved in the computation such as the binning parameters or the chromosomes to include in the analysis can be modified. When applied to published datasets, SNeP produced results closely comparable with those obtained in the original studies. The use of SNeP to estimate Ne trends can improve understanding of population demography in the recent past, provided a sufficient number of SNPs and their physical position in the genome are available. Binaries for the most common operating systems are available at https://sourceforge.net/projects/snepnetrends/.
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Reviewed by: David MacHugh, University College Dublin, Ireland; Yuri Tani Utsunomiya, Universidade Estadual Paulista(UNESP), Brazil
This article was submitted to Livestock Genomics, a section of the journal Frontiers in Genetics
Edited by: Paolo Ajmone Marsan, Università Cattolica del Sacro Cuore, Italy
ISSN:1664-8021
1664-8021
DOI:10.3389/fgene.2015.00109