NeTFactor, a framework for identifying transcriptional regulators of gene expression-based biomarkers.

ABSTRACT: Biological and regulatory mechanisms underlying many multi-gene expression-based disease biomarkers are often not readily evident. We describe an innovative framework, NeTFactor, that combines network analyses with gene expression data to identify transcription factors (TFs) that significantly and maximally regulate such a biomarker. NeTFactor uses a computationally-inferred context-specific gene regulatory network and applies topological, statistical, and optimization methods to identify regulator TFs. Application of NeTFactor to a multi-gene expression-based asthma biomarker identified ETS translocation variant 4 (ETV4) and peroxisome proliferator-activated receptor gamma (PPARG) as the biomarker's most significant TF regulators. siRNA-based knock down of these TFs in an airway epithelia

SUBMITTER: Ahsen ME 

PROVIDER: S-EPMC6737052 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature