English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We introduce a method to identify heritable microbiome communities when theinput is a pairwise dissimilarity matrix among all samples. Current methodstarget each taxon individually and are unable to take advantage of theirphylogenetic relationships. In contrast, our approach focuses on communityheritability by using the root-Unifrac to summarize the microbiome samplesthrough their pairwise dissimilarities while taking the phylogeny into account.The resulting dissimilarity matrix is then transformed into an outer productmatrix and further modeled through a Wishart distribution with the same set ofvariance components as in the univariate model. Directly modeling the entiredissimilarity matrix allows us to bypass any dimension reduction steps. Animportant contribution of our work is to prove the positive definiteness ofsuch outer product matrix, hence the applicability of the Wishart distribution.Simulation shows that this community heritability approach has higher powerthan existing methods to identify heritable groups of taxa. Empirical resultson the TwinsUK dataset are also provided.

Identifying Heritable Communities of Microbiome by Root-Unifrac and Wishart Distribution