MPLasso: Inferring microbial association networks using prior microbial knowledge.

ABSTRACT: Due to the recent advances in high-throughput sequencing technologies, it becomes possible to directly analyze microbial communities in human body and environment. To understand how microbial communities adapt, develop, and interact with the human body and the surrounding environment, one of the fundamental challenges is to infer the interactions among different microbes. However, due to the compositional and high-dimensional nature of microbial data, statistical inference cannot offer reliable results. Consequently, new approaches that can accurately and robustly estimate the associations (putative interactions) among microbes are needed to analyze such compositional and high-dimensional data. We propose a novel framework called Microbial Prior Lasso (MPLasso) which integrates graph learn

SUBMITTER: Lo C 

PROVIDER: S-EPMC5760079 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature