Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and int...

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Veröffentlicht in:Science China. Life sciences 2025, Vol.68 (1), p.5-102
Hauptverfasser: Sun, Fengying, Li, Haoyan, Sun, Dongqing, Fu, Shaliu, Gu, Lei, Shao, Xin, Wang, Qinqin, Dong, Xin, Duan, Bin, Xing, Feiyang, Wu, Jun, Xiao, Minmin, Zhao, Fangqing, Han, Jing-Dong J., Liu, Qi, Fan, Xiaohui, Li, Chen, Wang, Chenfei, Shi, Tieliu
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container_end_page 102
container_issue 1
container_start_page 5
container_title Science China. Life sciences
container_volume 68
creator Sun, Fengying
Li, Haoyan
Sun, Dongqing
Fu, Shaliu
Gu, Lei
Shao, Xin
Wang, Qinqin
Dong, Xin
Duan, Bin
Xing, Feiyang
Wu, Jun
Xiao, Minmin
Zhao, Fangqing
Han, Jing-Dong J.
Liu, Qi
Fan, Xiaohui
Li, Chen
Wang, Chenfei
Shi, Tieliu
description Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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subjects Animals
Biomedical and Life Sciences
CRISPR
Data Analysis
Genomics - methods
Humans
Information processing
Life Sciences
Metabolomics - methods
Phenotypes
Proteomes
Proteomics - methods
Review
Single-Cell Analysis - methods
Workflow
title Single-cell omics: experimental workflow, data analyses and applications
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