Scalable power analysis and effect size exploration of microbiome community differences with Evident (original) (raw)

New Results

, View ORCID ProfileDaniel McDonald, Antonio Gonzalez, View ORCID ProfileYoshiki Vázquez-Baeza, View ORCID ProfileLingjing Jiang, View ORCID ProfileCliment Casals-Pascual, Shyamal Peddada, Daniel Hakim, View ORCID ProfileAmanda Hazel Dilmore, View ORCID ProfileBrent Nowinski, Rob Knight

doi: https://doi.org/10.1101/2022.05.19.492684

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Abstract

Differentiating microbial communities among samples is a major objective in biomedicine. Quantifying the effect size of these differences allows researchers to understand the factors most associated with communities and to optimize the design and clinical resources required to address particular research questions. Here, we present Evident, a package for effect size calculations and power analysis on microbiome data and show that Evident scales to large datasets with numerous metadata covariates.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.