An adaptive association test for microbiome data. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Wu, Chong; Chen, Jun; Kim, Junghi; Pan, Wei
• Is Part Of: Genome medicine. Volume 8:Issue 1(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016-12
• Subjects: Genomics -- Periodicals; Medical genetics -- Periodicals; 616.042
• DOI: 10.1186/s13073-016-0302-3
• Languages: English
• ISSNs: 1756-994X

Abstract

Abstract There is increasing interest in investigating how the compositions of microbial communities are associated with human health and disease. Although existing methods have identified many associations, a proper choice of a phylogenetic distance is critical for the power of these methods. To assess an overall association between the composition of a microbial community and an outcome of interest, we present a novel multivariate testing method called aMiSPU, that is joint and highly adaptive over all observed taxa and thus high powered across various scenarios, alleviating the issue with the choice of a phylogenetic distance. Our simulations and real-data analyses demonstrated that the aMiSPU test was often more powerful than several competing methods while correctly controlling type I error rates. The R packageMiSPU is available athttps://github.com/ChongWu-Biostat/MiSPU and CRAN.