Poppr version 2


What is poppr?

Poppr is an R package designed for analysis of populations with mixed modes of sexual and clonal reproduction. It is built around the framework of adegenet’s genind and genlight objects and offers the following implementations:

New in version 2.0:

For full details, see the NEWS file or type in your R console:

news(Version >= "2.0.0", package = "poppr")


If you use poppr at all, please specify the version and cite:

Kamvar ZN, Tabima JF, Grünwald NJ. (2014) Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2:e281 https://doi.org/10.7717/peerj.281

If you use poppr in a presentation please mention it as the poppr R package, specify the version, and use our logo: (png) | (svg).

Additionally, if you use any following functionalities:

Please also cite:

Kamvar ZN, Brooks JC and Grünwald NJ (2015) Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Front. Genet. 6:208. doi: 10.3389/fgene.2015.00208

You can obtain citation information in R by typing:

citation(package = "poppr")



Binary versions for mac and windows are available for R ≥ 2.15.1 here.

To install, make sure R is at least version 2.15.1 (the authors recommend ≥ 3.0), and in your console, type:


If you want the absolute latest version of poppr, see about installing unreleased versions below.

Stable version

New features are occasionally added to {poppr}, but it can take time for it to get to CRAN. If you know that you want the latest version of {poppr}, (which will contain bug fixes and new features to be included in future releases), then you can use the custom R-Universe repository, which is updated hourly: https://zkamvar.r-universe.dev/builds

To install poppr from the R-Universe, you can use the following code:

universe <- c("https://zkamvar.r-universe.dev", "https://cloud.r-project.org")
install.packages("poppr", repos = universe)

The universe repository also contain up-to-date versions of {adegenet} and {hierfstat}, which are commonly used in conjunction with {poppr} and are notoriously out of date on CRAN.

Unstable/Development versions

All Development versions of {poppr} will be on GitHub, but need to be compiled.

To install this package from github, make sure you have the following:

For Linux users, make sure that the function getOption("unzip") returns "unzip" or "internal". If it does not, then run options(unzip = "internal").

Once you have {remotes} and a C compiler installed, you can use the install_github() function to install the current version from github.

All new features in testing will be released on different branches. These features will be in various stages of development and may or may not be documented. Install with caution. The below command would install features on the branch called “devel”. Note that these branches might be out of date from the main branch. Note: if you don’t have LaTeX installed, you should set build_vignettes = FALSE.

remotes::install_github(repo = "grunwaldlab/poppr@devel", build_vignettes = TRUE)

Help / Documentation

R documentation

To access a descriptive index of help files in poppr, type in your console:



A few vignettes have been written for poppr:

Title Command
Algorightms and Equations vignette("algo", "poppr")
Data import and manipulation vignette("poppr_manual", "poppr")
Multilocus Genotype Analysis vignette("mlg", "poppr")

User Group

Users who have any questions/comments/suggestions regarding any version of poppr (stable or development) should direct their comments to the Poppr google group


In Spring of 2014, Dr. Niklaus J. Grünwald, Dr. Sydney E. Everhart and Zhian N. Kamvar wrote a primer for population genetic analysis in R located at https://grunwaldlab.github.io/Population_Genetics_in_R.


Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. If you wish to contribute code to poppr, please fork the repository and create a pull request with your added feature.