Multilevel regularized regression for simultaneous taxa selection and network construction with metagenomic count data.

ABSTRACT:

Motivation

Identifying disease associated taxa and constructing networks for bacteria interactions are two important tasks usually studied separately. In reality, differentiation of disease associated taxa and correlation among taxa may affect each other. One genus can be differentiated because it is highly correlated with another highly differentiated one. In addition, network structures may vary under different clinical conditions. Permutation tests are commonly used to detect differences between networks in distinct phenotypes, and they are time-consuming.

Results

In this manuscript, we propose a multilevel regularized regression method to simultaneously identify taxa and construct networks. We also extend the framework to allow construction of a common network and differ

SUBMITTER: Liu Z 

PROVIDER: S-EPMC4382903 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature