Network-based analysis of omics data: the LEAN method.

ABSTRACT:

Motivation

Most computational approaches for the analysis of omics data in the context of interaction networks have very long running times, provide single or partial, often heuristic, solutions and/or contain user-tuneable parameters.

Results

We introduce local enrichment analysis (LEAN) for the identification of dysregulated subnetworks from genome-wide omics datasets. By substituting the common subnetwork model with a simpler local subnetwork model, LEAN allows exact, parameter-free, efficient and exhaustive identification of local subnetworks that are statistically dysregulated, and directly implicates single genes for follow-up experiments.Evaluation on simulated and biological data suggests that LEAN generally detects dysregulated subnetworks better, and reflects biolo

SUBMITTER: Gwinner F 

PROVIDER: S-EPMC5408824 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature