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ABSTRACT: Summary
While the R software is becoming a standard for the analysis of genetic data, classical population genetics tools are being challenged by the increasing availability of genomic sequences. Dedicated tools are needed for harnessing the large amount of information generated by next-generation sequencing technologies. We introduce new tools implemented in the adegenet 1.3-1 package for handling and analyzing genome-wide single nucleotide polymorphism (SNP) data. Using a bit-level coding scheme for SNP data and parallelized computation, adegenet enables the analysis of large genome-wide SNPs datasets using standard personal computers.Availability
adegenet 1.3-1 is available from CRAN: http://cran.r-project.org/web/packages/adegenet/. Information and support including a dedicated forum of discussion can be found on the adegenet website: http://adegenet.r-forge.r-project.org/. adegenet is released with a manual and four tutorials totalling over 300 pages of documentation, and distributed under the GNU General Public Licence (?2).Contact
t.jombart@imperial.ac.uk.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Jombart T
PROVIDER: S-EPMC3198581 | biostudies-literature | 2011 Nov
REPOSITORIES: biostudies-literature
Jombart Thibaut T Ahmed Ismaïl I
Bioinformatics (Oxford, England) 20110916 21
<h4>Summary</h4>While the R software is becoming a standard for the analysis of genetic data, classical population genetics tools are being challenged by the increasing availability of genomic sequences. Dedicated tools are needed for harnessing the large amount of information generated by next-generation sequencing technologies. We introduce new tools implemented in the adegenet 1.3-1 package for handling and analyzing genome-wide single nucleotide polymorphism (SNP) data. Using a bit-level cod ...[more]