Gap-com: general model selection criterion for sparse undirected gene networks with nontrivial community structure.

ABSTRACT: We introduce a new model selection criterion for sparse complex gene network modeling where gene co-expression relationships are estimated from data. This is a novel formulation of the gap statistic and it can be used for the optimal choice of a regularization parameter in graphical models. Our criterion favors gene network structure which differs from a trivial gene interaction structure obtained totally at random. We call the criterion the gap-com statistic (gap community statistic). The idea of the gap-com statistic is to examine the difference between the observed and the expected counts of communities (clusters) where the expected counts are evaluated using either data permutations or reference graph (the Erdős-Rényi graph) resampling. The latter represents a trivial gene network stru

SUBMITTER: Kuismin M 

PROVIDER: S-EPMC9210289 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature