Poppr: an R package for genetic analysis of populations with clonal or partially clonal reproduction
- Published
- Accepted
- Subject Areas
- Bioinformatics, Genetics, Microbiology, Mycology, Computational Science
- Keywords
- population genetics, clonality, genotypic diversity, index of association, Bruvo's distance, clone correction, minimum spanning networks, hierarchy, bootstrap, permutation
- Copyright
- © 2013 Kamvar et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Cite this article
- 2013. Poppr: an R package for genetic analysis of populations with clonal or partially clonal reproduction. PeerJ PrePrints 1:e161v1 https://doi.org/10.7287/peerj.preprints.161v1
Abstract
Many microbial, fungal, or oomcyete populations violate assumptions for population genetic analysis because these populations are clonal or partially clonal. 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, and/or mixed 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. 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/.