Detecting critical transition signals from single-cell transcriptomes to infer lineage-determining transcription factors.

ABSTRACT: Analyzing single-cell transcriptomes promises to decipher the plasticity, heterogeneity, and rapid switches in developmental cellular state transitions. Such analyses require the identification of gene markers for semi-stable transition states. However, there are nontrivial challenges such as unexplainable stochasticity, variable population sizes, and alternative trajectory constructions. By advancing current tipping-point theory-based models with feature selection, network decomposition, accurate estimation of correlations, and optimization, we developed BioTIP to overcome these challenges. BioTIP identifies a small group of genes, called critical transition signal (CTS), to characterize regulated stochasticity during semi-stable transitions. Although methods rooted in different theories

SUBMITTER: Yang XH 

PROVIDER: S-EPMC9458468 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature