Improving gene network inference with graph wavelets and making insights about ageing-associated regulatory changes in lungs.

ABSTRACT: Using gene-regulatory-networks-based approach for single-cell expression profiles can reveal unprecedented details about the effects of external and internal factors. However, noise and batch effect in sparse single-cell expression profiles can hamper correct estimation of dependencies among genes and regulatory changes. Here, we devise a conceptually different method using graphwavelet filters for improving gene network (GWNet)-based analysis of the transcriptome. Our approach improved the performance of several gene network-inference methods. Most Importantly, GWNet improved consistency in the prediction of gene regulatory network using single-cell transcriptome even in the presence of batch effect. The consistency of predicted gene network enabled reliable estimates of changes in the in

SUBMITTER: Mishra S 

PROVIDER: S-EPMC7799288 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature