Open AccessA rarefaction-without-resampling extension of PERMANOVA for testing presence–absence associations in the microbiome
Author(s) -
YiJuan Hu,
Glen A. Satten
Publication year - 2022
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btac399
Subject(s) - unifrac , resampling , jaccard index , overdispersion , statistics , covariate , rarefaction (ecology) , confounding , mathematics , distance matrix , computer science , biology , count data , algorithm , ecology , poisson distribution , cluster analysis , genetics , 16s ribosomal rna , bacteria , species diversity
PERMANOVA is currently the most commonly used method for testing community-level hypotheses about microbiome associations with covariates of interest. PERMANOVA can test for associations that result from changes in which taxa are present or absent by using the Jaccard or unweighted UniFrac distance. However, such presence-absence analyses face a unique challenge: confounding by library size (total sample read count), which occurs when library size is associated with covariates in the analysis. It is known that rarefaction (subsampling to a common library size) controls this bias but at the potential costs of information loss and the introduction of a stochastic component into the analysis.