A powerful weighted statistic for detecting group differences of directed biological networks.

ABSTRACT: Complex disease is largely determined by a number of biomolecules interwoven into networks, rather than a single biomolecule. Different physiological conditions such as cases and controls may manifest as different networks. Statistical comparison between biological networks can provide not only new insight into the disease mechanism but statistical guidance for drug development. However, the methods developed in previous studies are inadequate to capture the changes in both the nodes and edges, and often ignore the network structure. In this study, we present a powerful weighted statistical test for group differences of directed biological networks, which is independent of the network attributes and can capture the changes in both the nodes and edges, as well as simultaneously accounting f

SUBMITTER: Yuan Z 

PROVIDER: S-EPMC5054825 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature