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

被引:0
|
作者
Fengying Sun [1 ]
Haoyan Li [2 ]
Dongqing Sun [3 ,4 ]
Shaliu Fu [3 ,5 ,6 ,7 ]
Lei Gu [8 ]
Xin Shao [2 ,9 ]
Qinqin Wang [8 ]
Xin Dong [3 ,4 ]
Bin Duan [3 ,5 ,6 ,7 ]
Feiyang Xing [3 ,4 ]
Jun Wu [10 ]
Minmin Xiao [1 ]
Fangqing Zhao [11 ]
JingDong JHan [12 ]
Qi Liu [3 ,5 ,6 ,7 ]
Xiaohui Fan [2 ,9 ,13 ]
Chen Li [8 ]
Chenfei Wang [3 ,4 ]
Tieliu Shi [1 ,10 ,14 ]
机构
[1] Department of Clinical Laboratory,the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City)
[2] Pharmaceutical Informatics Institute,College of Pharmaceutical Sciences,Zhejiang University
[3] Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University),Ministry of Education,Orthopaedic Department,Tongji Hospital,Bioinformatics Department,School of Life Sciences and Technology,Tongji University
[4] Frontier Science Center for Stem Cells,School of Life Sciences and Technology,Tongji University
[5] Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine,Shanghai East Hospital,Bioinformatics Department,School of Life Sciences and Technology,Tongji University
[6] Research Institute of Intelligent Computing,Zhejiang Lab
[7] Shanghai Research Institute for Intelligent Autonomous Systems
[8] Center for Single-cell Omics,School of Public Health,Shanghai Jiao Tong University School of Medicine
[9] National Key Laboratory of Chinese Medicine Modernization,Innovation Center of Yangtze River Delta,Zhejiang University
[10] Center for Bioinformatics and Computational Biology,Shanghai Key Laboratory of Regulatory Biology,the Institute of Biomedical Sciences and School of Life Sciences,East China Normal University
[11] Beijing Institutes of Life Science,Chinese Academy of Sciences
[12] Peking-Tsinghua Center for Life Sciences,Academy for Advanced Interdisciplinary Studies,Center for Quantitative Biology (CQB),Peking University
[13] Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases,Women's Hospital,Zhejiang University School of Medicine
[14] Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE,School of Statistics,East China Normal
关键词
D O I
暂无
中图分类号
Q811.4 [生物信息论];
学科分类号
0711 ; 0831 ;
摘要
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 sc RNA-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.
引用
收藏
页码:5 / 102
页数:98
相关论文
共 50 条
  • [21] Applications of single-cell multi-omics in liver cancer
    Peeters, Frederik
    Cappuyns, Sarah
    Pique-Gili, Marta
    Phillips, Gino
    Verslype, Chris
    Lambrechts, Diether
    Dekervel, Jeroen
    JHEP REPORTS, 2024, 6 (07)
  • [22] Advances and applications of single-cell omics technologies in plant research
    Mo, Yajin
    Jiao, Yuling
    PLANT JOURNAL, 2022, 110 (06): : 1551 - 1563
  • [23] A focus on single-cell omics
    不详
    NATURE REVIEWS GENETICS, 2023, 24 (08) : 485 - 485
  • [24] BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization
    Taverna, Federico
    Goveia, Jermaine
    Karakach, Tobias K.
    Khan, Shawez
    Rohlenova, Katerina
    Treps, Lucas
    Subramanian, Abhishek
    Schoonjans, Luc
    Dewerchin, Mieke
    Eelen, Guy
    Carmeliet, Peter
    NUCLEIC ACIDS RESEARCH, 2020, 48 (W1) : W385 - W394
  • [25] A focus on single-cell omics
    Nature Reviews Genetics, 2023, 24 : 485 - 485
  • [26] A Python library for probabilistic analysis of single-cell omics data
    Adam Gayoso
    Romain Lopez
    Galen Xing
    Pierre Boyeau
    Valeh Valiollah Pour Amiri
    Justin Hong
    Katherine Wu
    Michael Jayasuriya
    Edouard Mehlman
    Maxime Langevin
    Yining Liu
    Jules Samaran
    Gabriel Misrachi
    Achille Nazaret
    Oscar Clivio
    Chenling Xu
    Tal Ashuach
    Mariano Gabitto
    Mohammad Lotfollahi
    Valentine Svensson
    Eduardo da Veiga Beltrame
    Vitalii Kleshchevnikov
    Carlos Talavera-López
    Lior Pachter
    Fabian J. Theis
    Aaron Streets
    Michael I. Jordan
    Jeffrey Regier
    Nir Yosef
    Nature Biotechnology, 2022, 40 : 163 - 166
  • [27] Computational Methods for Single-Cell Imaging and Omics Data Integration
    Watson, Ebony Rose
    Taherian Fard, Atefeh
    Mar, Jessica Cara
    FRONTIERS IN MOLECULAR BIOSCIENCES, 2022, 8
  • [28] Clustering single-cell multi-omics data with MoClust
    Yuan, Musu
    Chen, Liang
    Deng, Minghua
    BIOINFORMATICS, 2023, 39 (01)
  • [29] Intricacies of single-cell multi-omics data integration
    Rautenstrauch, Pia
    Vlot, Anna Hendrika Cornelia
    Saran, Sepideh
    Ohler, Uwe
    TRENDS IN GENETICS, 2022, 38 (02) : 128 - 139
  • [30] Applications of single-cell omics for chimeric antigen receptor T cell therapy
    Ghaffari, Sasan
    Saleh, Mahshid
    Akbari, Behnia
    Ramezani, Faezeh
    Mirzaei, Hamid Reza
    IMMUNOLOGY, 2024, 171 (03) : 339 - 364