A general framework for association analysis of microbial communities on a taxonomic tree.

ABSTRACT:

Motivation

: Association analysis of microbiome composition with disease-related outcomes provides invaluable knowledge towards understanding the roles of microbes in the underlying disease mechanisms. Proper analysis of sparse compositional microbiome data is challenging. Existing methods rely on strong assumptions on the data structure and fail to pinpoint the associated microbial communities.

Results

: We develop a general framework to: (i) perform robust association tests for the microbial community that exhibits arbitrary inter-taxa dependencies; (ii) localize lineages on the taxonomic tree that are associated with covariates (e.g. disease status); and (iii) assess the overall association of the whole microbial community with the covariates. Unlike existing methods for

SUBMITTER: Tang ZZ 

PROVIDER: S-EPMC5408811 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature