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PMID: 22820204 Published · ppublish English Journal Article

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update.

Bioinformatics (Oxford, England) ·Vol. 28 ·No. 19 ·2012-10-01 ·Pages 2537-9

Peakall R, Smouse PE

Abstract

GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G'(ST), G''(ST), Jost's D(est) and F'(ST) through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. rod.peakall@anu.edu.au.

MeSH Terms
Computational Biology/methods Gene Frequency Genetic Markers Genetics, Population/education,methods Haplotypes Linkage Disequilibrium Software User-Computer Interface
Chemicals
Genetic Markers
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Peakall Rod
Evolution, Ecology and Genetics, Research School of Biology, The Australian National University, Canberra ACT 0200, Australia. rod.peakall@anu.edu.au
Smouse Peter E
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Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4811
DOI
10.1093/bioinformatics/bts460
Email
rod.peakall@anu.edu.au
Published
2012-10-01
Epub
2012-00-20
Pages
2537-9
Language
English
Region
England
NLM ID
9808944
PMCID
PMC3463245
Subset
IM
External Links
PubMed source DOI: 10.1093/bioinformatics/bts460 PMC Full Text View journal details
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