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coda4microbiome: compositional data analysis for microbiome studies

Calle, M. L.; Susin, A.

2022-06-11 microbiology
10.1101/2022.06.09.495511 bioRxiv
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MotivationOne of the main challenges of microbiome analysis is its compositional nature that if ig-nored can lead to spurious results. This is especially critical when dealing with microbiome variable selection since classical differential abundance tests are known to provide large false positive rates. ResultsWe developed coda4microbiome, a new R package for analyzing microbiome data within the Compositional Data Analysis (CoDA) framework in both, cross-sectional and longitudinal studies. The core functions of the library are aimed at the identification of microbial signatures and involve variable selection in generalized linear models with compositional covariates. All algorithms are accompanied by meaningful graphical representations that allow a better interpretation of the results. Availabilitycoda4microbiome is implemented as an R package and is available at CRAN https://cran.r-project.org/web/packages/coda4microbiome/index.html. Contactmalu.calle@uvic.cat Supplementary informationcoda4microbiome project website: https://malucalle.github.io/coda4mi-crobiome/.

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