An adaptive association test for microbiome data

作者：Wu, Chong; Chen, Jun; Kim, Junghi; Pan, Wei^*

来源：Genome Medicine, 2016, 8(1): 56.

DOI：10.1186/s13073-016-0302-3

• DIFFERENTIAL ABUNDANCE ANALYSIS
• GUT MICROBIOME
• REGRESSION
• DIVERSITY
• UNIFRAC

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 package MiSPU is available at https://github.com/ChongWu-Biostat/MiSPU and CRAN.

• 出版日期2016-5-19