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PeerJ. 2014 Mar 4;2:e281. doi: 10.7717/peerj.281. eCollection 2014.

Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction.

Author information

1
Department of Botany and Plant Pathology, Oregon State University , Corvallis, OR , USA.
2
Department of Botany and Plant Pathology, Oregon State University , Corvallis, OR , USA ; Horticultural Crops Research Laboratory, USDA-ARS , Corvallis, OR , USA.

Abstract

Many microbial, fungal, or oomcyete populations violate assumptions for population genetic analysis because these populations are clonal, admixed, partially clonal, and/or sexual. Furthermore, few tools exist that are specifically designed for analyzing data from clonal populations, making analysis difficult and haphazard. We developed the R package poppr providing unique tools for analysis of data from admixed, clonal, mixed, and/or sexual populations. Currently, poppr can be used for dominant/codominant and haploid/diploid genetic data. Data can be imported from several formats including GenAlEx formatted text files and can be analyzed on a user-defined hierarchy that includes unlimited levels of subpopulation structure and clone censoring. New functions include calculation of Bruvo's distance for microsatellites, batch-analysis of the index of association with several indices of genotypic diversity, and graphing including dendrograms with bootstrap support and minimum spanning networks. While functions for genotypic diversity and clone censoring are specific for clonal populations, several functions found in poppr are also valuable to analysis of any populations. A manual with documentation and examples is provided. Poppr is open source and major releases are available on CRAN: http://cran.r-project.org/package=poppr. More supporting documentation and tutorials can be found under 'resources' at: http://grunwaldlab.cgrb.oregonstate.edu/.

KEYWORDS:

Bootstrap; Bruvo’s distance; Clonality; Clone correction; Genotypic diversity; Hierarchy; Index of association; Minimum spanning networks; Permutation; Population genetics

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