Abstract
SummaryWe present a new R package admixr, which provides a convenient interface for performing reproducible population genetic analyses (f3, D, f4, f4-ratio, qpWave and qpAdm), as implemented by command-line programs in the ADMIXTOOLS software suite. In a traditional ADMIXTOOLS workflow, the user must first generate a set of text configuration files tailored to each individual analysis, often using a combination of shell scripting and manual text editing. The non-tabular output files then need to be parsed to extract values of interest prior to further analyses. Our package simplifies this process by automating all low-level configuration and parsing steps, making analyses as simple as running a single R command. Furthermore, we provide a set of R functions for processing, filtering and manipulating datasets in the EIGENSTRAT format. By unifying all steps of the workflow under a single R framework, this package enables the automation of analytic pipelines, significantly improving the reproducibility of population genetic studies.Availability and implementationThe source code of the R package is available under the MIT license. Installation instructions, reference manual and a tutorial can be found on the package website at https://bioinf.eva.mpg.de/admixr.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
The growing number of ancient and modern genome sequences have transformed our understanding of the evolutionary history of humans and other species
Summary: We present a new R package admixr, which provides a convenient interface for performing reproducible population genetic analyses (f3, D, f4, f4-ratio, qpWave and qpAdm), as implemented by command-line programs in the ADMIXTOOLS software suite
In a traditional ADMIXTOOLS workflow, the user must first generate a set of text configuration files tailored to each individual analysis, often using a combination of shell scripting and manual text editing
Summary
The growing number of ancient and modern genome sequences have transformed our understanding of the evolutionary history of humans and other species. After running an ADMIXTOOLS command on the command-line, the user needs to extract relevant values from a non-tabular text file before they can be imported into software such as R for further analysis and plotting. This workflow is slow and potentially errorprone, especially if the user wishes to quickly iterate through different hypotheses involving many different populations or samples. It makes it challenging to conduct fully reproducible research To overcome these challenges, we present a new R package for population admixture analyses which utilizes the ADMIXTOOLS software suite for the underlying calculations, but that provides a unified and convenient R interface.
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