A fast small-sample kernel independence test for microbiome community-level association analysis.

ABSTRACT: To fully understand the role of microbiome in human health and diseases, researchers are increasingly interested in assessing the relationship between microbiome composition and host genomic data. The dimensionality of the data as well as complex relationships between microbiota and host genomics pose considerable challenges for analysis. In this article, we apply a kernel RV coefficient (KRV) test to evaluate the overall association between host gene expression and microbiome composition. The KRV statistic can capture nonlinear correlations and complex relationships among the individual data types and between gene expression and microbiome composition through measuring general dependency. Testing proceeds via a similar route as existing tests of the generalized RV coefficients and allows

SUBMITTER: Zhan X 

PROVIDER: S-EPMC5592124 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature