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Admixr-R package for reproducible analyses using ADMIXTOOLS.


ABSTRACT:

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. 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 implementation

The 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.

SUBMITTER: Petr M 

PROVIDER: S-EPMC6736366 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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admixr-R package for reproducible analyses using ADMIXTOOLS.

Petr Martin M   Vernot Benjamin B   Kelso Janet J  

Bioinformatics (Oxford, England) 20190901 17


<h4>Summary</h4>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. The non-tabular output files th  ...[more]

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