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@article{Paradis:2016:10.1111/1755-0998.12577,
author = {Paradis, E and Gosselin, T and Goudet, J and Jombart, T and Schliep, K},
doi = {10.1111/1755-0998.12577},
journal = {Molecular Ecology Resources},
pages = {54--66},
title = {Linking genomics and population genetics with R},
url = {http://dx.doi.org/10.1111/1755-0998.12577},
volume = {17},
year = {2016}
}

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TY  - JOUR
AB  - Population genetics and genomics have developed and been treated as independent fields of study despite having common roots. The continuous progress of sequencing technologies is contributing to (re-)connect these two disciplines. We review the challenges faced by data analysts and software developers when handling very big genetic data sets collected on many individuals. We then expose how R, as a computing language and development environment, proposes some solutions to meet these challenges. We focus on some specific issues that are often encountered in practice: handling and analysing SNP data, handling and reading VCF files, analysing haplotypes and linkage disequilibrium, and performing multivariate analyses. We illustrate these implementations with some analyses of three recently published data sets that contain between 60,000 and 1,000,000 loci. We conclude with some perspectives on future developments of R software for population genomics. This article is protected by copyright. All rights reserved.
AU  - Paradis,E
AU  - Gosselin,T
AU  - Goudet,J
AU  - Jombart,T
AU  - Schliep,K
DO  - 10.1111/1755-0998.12577
EP  - 66
PY  - 2016///
SN  - 1755-0998
SP  - 54
TI  - Linking genomics and population genetics with R
T2  - Molecular Ecology Resources
UR  - http://dx.doi.org/10.1111/1755-0998.12577
UR  - http://hdl.handle.net/10044/1/39441
VL  - 17
ER  -

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