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Activity Number: 251 - Statistical Advances in Microbiome Research from Theory to Application
Type: Invited
Date/Time: Tuesday, August 4, 2020 : 1:00 PM to 2:50 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #309583
Title: A Powerful Microbial Group Association Test Based on the Higher Criticism Analysis
Author(s): Ni Zhao* and Hyunwook Koh
Companies: Johns Hopkins University, Bloomberg School of Public Health and Johns Hopkins University
Keywords: higher criticism; adaptive test; community level analysis

In human microbiome studies, it is essential to evaluate the association between microbial group (e.g., community or clade) and a host phenotype of interest. Many microbial group association tests have been proposed, taking into account the unique features of the microbiome data (e.g., high-dimensionality, compositionality, phylogenetic relationship). These tests generally fall in the class of aggregation tests which amplify the overall association by combining all the underlying microbial signals; as such, they are powerful when many species are associated (i.e., low sparsity). In practice, the microbial association signals can be highly sparse, a situation in which we have difficulty to discover the group association. Hence, here we introduce a powerful microbial group association test for sparse microbial association signals, namely, microbiome higher criticism analysis (MiHC). MiHC is a data-driven test taken in a search space by tailoring the higher criticism test to incorporate phylogenetic information and/or modulate sparsity levels. Our simulations show that MiHC maintains a high power at different phylogenetic relevance and sparsity levels with correct type I error control

Authors who are presenting talks have a * after their name.

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