RedPATH: Reconstructing the Pseudo Development Time of Cell Lineages in Single-cell RNA-seq Data and Applications in Cancer.

ABSTRACT: The recent advancement of single-cell RNA sequencing (scRNA-seq) technologies facilitates the study of cell lineages in developmental processes and cancer. In this study, we developed a computational method, called redPATH, to reconstruct the pseudo developmental time of cell lineages using a consensus asymmetric Hamiltonian path algorithm. Besides, we developed a novel approach to visualize the trajectory development and implemented visualization methods to provide biological insights. We validated the performance of redPATH by segmenting different stages of cell development on multiple neural stem cell and cancer datasets, as well as other single-cell transcriptome data. In particular, we identified a stem cell-like subpopulation in malignant glioma cells. These cells express known proli

SUBMITTER: Xie K 

PROVIDER: S-EPMC8602773 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature