Linking genomics and population genetics with R.

Détails

ID Serval
serval:BIB_90179BE9C8A4
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Linking genomics and population genetics with R.
Périodique
Molecular ecology resources
Auteur(s)
Paradis E., Gosselin T., Goudet J., Jombart T., Schliep K.
ISSN
1755-0998 (Electronic)
ISSN-L
1755-098X
Statut éditorial
Publié
Date de publication
04/2017
Volume
17
Numéro
1
Pages
54-66
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
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 single-nucleotide polymorphism data, handling and reading variant call format 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.

Mots-clé
Biostatistics/methods, Computational Biology/methods, Genetics, Population/methods, Genomics/methods, Haplotypes, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Software
Pubmed
Open Access
Oui
Création de la notice
12/01/2017 16:27
Dernière modification de la notice
08/05/2019 21:57
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