PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances.

ABSTRACT:

Motivation

Recent advances in sequencing technology have made it possible to obtain high-throughput data on the composition of microbial communities and to study the effects of dysbiosis on the human host. Analysis of pairwise intersample distances quantifies the association between the microbiome diversity and covariates of interest (e.g. environmental factors, clinical outcomes, treatment groups). In the design of these analyses, multiple choices for distance metrics are available. Most distance-based methods, however, use a single distance and are underpowered if the distance is poorly chosen. In addition, distance-based tests cannot flexibly handle confounding variables, which can result in excessive false-positive findings.

Results

We derive presence-weighted UniFrac to

SUBMITTER: Tang ZZ 

PROVIDER: S-EPMC5013911 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature