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

Shreya Mishra, Vibhor Kumar
2020 bioRxiv   pre-print
Using gene-regulatory-networks based approach for single-cell expression profiles can reveal unprecedented details about the effects of external and internal stress on cells. 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 graph-wavelet filters for improving gene-network (GWNet) based analysis of the transcriptome. Our approach improved
more » ... 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 presence of batch effect. Consistency of predicted gene-network enabled reliable estimates of changes in the influence of genes not highlighted by differential-expression analysis. Applying GWNet on the single-cell transcriptome profile of lung cells, revealed biologically-relevant changes in the influence of pathways and master-regulators due to ageing. Surprisingly, the regulatory influence of ageing on pneumocytes type II cells showed noticeable similarity with patterns due to effect of novel coronavirus infection in Human Lung.
doi:10.1101/2020.07.24.219196 fatcat:rww7gelmojd5zihj3p4ciyleby