Published in

Oxford University Press, Bioinformatics, 11(37), p. 1595-1597, 2020

DOI: 10.1093/bioinformatics/btaa951

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MiRKAT: kernel machine regression-based global association tests for the microbiome

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Abstract Summary Distance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and high-dimensional outcomes. Omnibus tests allow simultaneous consideration of multiple distance and dissimilarity measures, providing higher power across a range of simulation scenarios. Two measures of effect size, a modified R-squared coefficient and a kernel RV coefficient, are incorporated to allow comparison of effect sizes across multiple kernels. Availability and implementation MiRKAT is available on CRAN as an R package. Supplementary information Supplementary data are available at Bioinformatics online.