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The goal of tidypopgen is to provide a tidy grammar of
population genetics, facilitating the manipulation and analysis of
biallelic single nucleotide polymorphisms (SNPs).
tidypopgen scales to very large genetic datasets by storing
genotypes on disk, and performing operations on them in chunks, without
ever loading all data in memory.
You can install the release version of tidypopgen from
CRAN:
install.packages("tidypopgen")You can install the latest development version directly from r-universe (recommended):
install.packages('tidypopgen', repos = c('https://evolecolgroup.r-universe.dev',
'https://cloud.r-project.org'))Alternatively, you can install tidypopgenusing
devtools (but you might need to set up your development
environment, which can be a bit more complex):
install.packages("devtools")
devtools::install_github("EvolEcolGroup/tidypopgen")There are several vignettes designed to teach you how to use
tidypopgen. A short introduction to the package is
available in the ‘introduction’
vignette. A more detailed and technical description of the grammar
of population genetics, explaining how to manipulate individuals and
loci, is available in the ‘grammar’
vignette.
The ‘quality
control’ vignette illustrates the tidypopgen functions
that help running a full QC of a dataset before analysis.
The ‘population
genetic analysis’ vignette provides a fully annotated example of how
to run various population genetics analyses with
tidypopgen.
We also provide a ‘PLINK
cheatsheet’ aimed at translating common tasks performed in PLINK
into tidypopgen commands.
There is also an article showing how manage aDNA sample that have been coded as pseudohaploids, including how to project ancient DNA data onto a PCA fitted to modern data and prepare data for admixtools: ‘aDNA pseudohaploids’ article.
Finally, tidypopgen is fast and can handle large
datasets easily. See a ‘benchmark’
article using the HGDP, a dataset of over 1000 individuals typed for
650k SNPs. We can load the data, clean it, run imputation, PCA and
pairwise Fst among 51 populations in less than 20 seconds on a powerful
desktop (and less than a minute on a laptop).
If something does not work, check the issues on
GitHub to see whether the problem has already been reported. If not,
feel free to create an new issue. Please make sure you have updated to
the latest version of tidypopgen on r-universe/Github, as
well as updating all other packages on your system, and provide a reproducible example for the
developers to investigate the problem. Ideally, try to create a
minimalistic dataset that reproduces the error, as it will be much
easier (and thus faster!) for the developers to track down the
problem.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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