Unraveling the timeline of gene expression: A pseudotemporal trajectory analysis of single-cell RNA sequencing data.

ABSTRACT:

Background

Single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed in recent years. The droplet-based single cell platforms enable the profiling of gene expression in tens of thousands of cells per sample. The goal of a typical scRNA-seq analysis is to identify different cell subpopulations and their respective marker genes. Additionally, trajectory analysis can be used to infer the developmental or differentiation trajectories of cells.

Methods

This article demonstrates a comprehensive workflow for performing trajectory inference and time course analysis on a multi-sample single-cell RNA-seq experiment of the mouse mammary gland. The workflow uses open-source R software packages and covers all steps of the analysis pipeline, including quality control, dou

SUBMITTER: Cheng J 

PROVIDER: S-EPMC10663991 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature