General Information
| Description | Association test for microbial community composition that accommodates confounders and multiple distances |
| Homepage | https://medschool.vanderbilt.edu/tang-lab/software/miProfile |
Publications
PERMANOVA-S: association test for microbial community composition that
accommodates confounders and multiple distances
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 complement the existing
UniFrac distances for more powerful detection of the variation in species richness. We
develop PERMANOVA-S, a new distance-based method that tests the association of microbiome
composition with any covariates of interest. PERMANOVA-S improves the commonly-used
Permutation Multivariate Analysis of Variance (PERMANOVA) test by allowing flexible
confounder adjustments and ensembling multiple distances. We conducted extensive
simulation studies to evaluate the performance of different distances under various
patterns of association. Our simulation studies demonstrate that the power of the test
relies on how well the selected distance captures the nature of the association. The
PERMANOVA-S unified test combines multiple distances and achieves good power regardless of
the patterns of the underlying association. We demonstrate the usefulness of our approach
by reanalyzing several real microbiome datasets.
Availability and Implementation:
miProfile software is freely available at https://medschool.vanderbilt.edu/tang-lab/software/miProfile .
Contact:
z.tang@vanderbilt.edu or g.chen@vanderbilt.edu
Supplementary information:
Supplementary data are available at Bioinformatics online.
Related Tools
ape 3.0
Published April 2012
New tools for distance-based phylogenetics and evolutionary analysis in R
MGAS
Published November 2014
A powerful tool for multivariate gene-based genome-wide association analysis
MetaCoMET
Published August 2016
A web platform for discovery and visualization of the core microbiome
FAIR Evaluation
Sorry, you must be signed in to evaluate this object.
