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DAtest: a framework for choosing differential abundance or expression method

View ORCID ProfileJakob Russel, Jonathan Thorsen, Asker D. Brejnrod, Hans Bisgaard, Søren J. Sørensen, Mette Burmølle
doi: https://doi.org/10.1101/241802
Jakob Russel
1Section for Microbiology, Faculty of Science, University of Copenhagen, 2100 Ø, Denmark
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Jonathan Thorsen
2COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
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Asker D. Brejnrod
3Section for Metabolic Genetics, Faculty of Health, University of Copenhagen, 2100 Ø, Denmark
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Hans Bisgaard
2COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
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Søren J. Sørensen
1Section for Microbiology, Faculty of Science, University of Copenhagen, 2100 Ø, Denmark
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Mette Burmølle
1Section for Microbiology, Faculty of Science, University of Copenhagen, 2100 Ø, Denmark
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Abstract

DAtest is an R package for directly comparing different statistical methods for differential abundance and expression analysis on a dataset of interest; be it data from RNA-seq, proteomics, metabolomics or a microbial marker-gene survey. A myriad of statistical methods exists for conducting these analyses, and with this tool we give the analyst an empirical foundation for choosing a method suitable for a specific dataset. The package supports categorical and quantitative variables, paired/block experimental designs, and the inclusion of covariates. It is freely available at GitHub: https://github.com/Russel88/DAtest along with detailed instructions.

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Posted January 02, 2018.
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DAtest: a framework for choosing differential abundance or expression method
Jakob Russel, Jonathan Thorsen, Asker D. Brejnrod, Hans Bisgaard, Søren J. Sørensen, Mette Burmølle
bioRxiv 241802; doi: https://doi.org/10.1101/241802
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DAtest: a framework for choosing differential abundance or expression method
Jakob Russel, Jonathan Thorsen, Asker D. Brejnrod, Hans Bisgaard, Søren J. Sørensen, Mette Burmølle
bioRxiv 241802; doi: https://doi.org/10.1101/241802

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