%0 Journal Article %A Gibraan Rahman %A Daniel McDonald %A Antonio Gonzalez %A Yoshiki Vázquez-Baeza %A Lingjing Jiang %A Climent Casals-Pascual %A Shyamal Peddada %A Daniel Hakim %A Amanda Hazel Dilmore %A Brent Nowinski %A Rob Knight %T Scalable power analysis and effect size exploration of microbiome community differences with Evident %D 2022 %R 10.1101/2022.05.19.492684 %J bioRxiv %P 2022.05.19.492684 %X 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 StatementThe authors have declared no competing interest. %U https://www.biorxiv.org/content/biorxiv/early/2022/05/20/2022.05.19.492684.full.pdf