Phylogeny-Based Kernels with Application to Microbiome Association Studies View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Jian Xiao , Jun Chen

ABSTRACT

The human microbiome, the collection of the microorganisms and their genomes associated with the human body, has received tremendous attention recently due to its important role in human health and disease. Next generation sequencing technology opens a new era for microbiome research via direct sequencing of the microbial DNA. One widely used approach sequences the bacterial 16S rRNA gene to profile the bacterial content of the human microbiome, resulting in a sparse species abundance table, together with a phylogenetic tree among species. Due to the complex interaction between bacterial species and the environment, linear model is not appropriate for microbiome data. Kernel methods, which allow modeling nonlinear relationship, have become increasingly popular for microbiome data. Moreover, kernel methods allow easy incorporation of prior structure information by defining a problem-specific kernel function. For microbiome data, the phylogenetic tree provides important prior information about how these bacterial species are related, and incorporating the phylogenetic tree into analysis can potentially improve the efficiency and power of the analysis. While there are methods for converting the phylogeny-based distance measures into kernels, a formal kernel function that allows flexible integration of the tree does not exist. Here we provide a three-parameter phylogeny-based kernel, which allows modeling a wide range of nonlinear relationships. Each parameter has a nice biological interpretation and, by tuning the parameter, we can gain insights about how the microbiome interacts with the environment. We demonstrated the performance of the phylogeny-based kernel in the context of kernel machine-based microbiome association test. We show that the test based on our new kernel outperforms that based on traditional distance-converted kernels. We finally applied the phylogeny-based kernel to a real gut microbiome data from a diet-microbiome association study. We identified more nutrients associated with the gut microbiome using the phylogeny-based kernel. More... »

PAGES

217-237

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-69416-0_13

DOI

http://dx.doi.org/10.1007/978-3-319-69416-0_13

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100460191


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