viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia

被引：0
|
作者：
El-ad David Amir
Kara L Davis
Michelle D Tadmor
Erin F Simonds
Jacob H Levine
Sean C Bendall
Daniel K Shenfeld
Smita Krishnaswamy
Garry P Nolan
Dana Pe'er
机构：
[1] Columbia Initiative for Systems Biology,Department of Biological Sciences
[2] Columbia University,Department of Microbiology and Immunology
[3] Baxter Laboratory in Stem Cell Biology,undefined
[4] Stanford University,undefined
来源：
Nature Biotechnology | 2013年 / 31卷
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A new tool to visualize high-dimensional single-cell data, when integrated with mass cytometry, reveals phenotypic heterogeneity of human leukemia.
引用
收藏
页码：545 / 552
页数：7
相关论文
共 50 条
  • [41] Microbial individuality: how single-cell heterogeneity enables population level strategies
    Martins, Bruno M. C.
    Locke, James O. W.
    CURRENT OPINION IN MICROBIOLOGY, 2015, 24 : 104 - 112
  • [42] High Dimensional Single-Cell Profiling Identifies Immune and Metabolic Heterogeneity in Immune Thrombocytopenia
    Yang, Li-Ping
    Fu, Hai-Xia
    Zhao, Peng
    Wu, Jin
    Huang, Qiu-Sha
    Zhang, Yuan-Yuan
    Kong, Jun
    Wang, Zhi-Dong
    Liu, Jing
    Liu, Kaiyan
    Huang, Xiao Jun
    Zhang, Xiaohui
    BLOOD, 2023, 142
  • [43] Single-cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma
    Zheng, Hongping
    Pomyen, Yotsawat
    Hernandez, Maria Olga
    Li, Caiyi
    Livak, Ferenc
    Tang, Wei
    Dang, Hien
    Greten, Tim F.
    Davis, Jeremy L.
    Zhao, Yongmei
    Mehta, Monika
    Levin, Yelena
    Shetty, Jyoti
    Tran, Bao
    Budhu, Anuradha
    Wang, Xin Wei
    HEPATOLOGY, 2018, 68 (01) : 127 - 140
  • [44] Optimized multiplex immunofluorescence single-cell analysis reveals tuft cell heterogeneity
    McKinley, Eliot T.
    Sui, Yunxia
    Al-Kofahi, Yousef
    Millis, Bryan A.
    Tyska, Matthew J.
    Roland, Joseph T.
    Santamaria-Pang, Alberto
    Ohland, Christina L.
    Jobin, Christian
    Franklin, Jeffrey L.
    Lau, Ken S.
    Gerdes, Michael J.
    Coffey, Robert J.
    JCI INSIGHT, 2017, 2 (11)
  • [45] Measuring Single-Cell Phenotypic Growth Heterogeneity Using a Microfluidic Cell Volume Sensor
    Wenyang Jing
    Brendan Camellato
    Ian J. Roney
    Mads Kaern
    Michel Godin
    Scientific Reports, 8
  • [46] Measuring Single-Cell Phenotypic Growth Heterogeneity Using a Microfluidic Cell Volume Sensor
    Jing, Wenyang
    Camellato, Brendan
    Roney, Ian J.
    Kaern, Mads
    Godin, Michel
    SCIENTIFIC REPORTS, 2018, 8
  • [47] Differential Variation Analysis Enables Detection of Tumor Heterogeneity Using Single-Cell RNA-Sequencing Data
    Davis-Marcisak, Emily F.
    Sherman, Thomas D.
    Orugunta, Pranay
    Stein-O'Brien, Genevieve L.
    Puram, Sidharth V.
    Torres, Evanthia T. Roussos
    Hopkins, Alexander C.
    Jaffee, Elizabeth M.
    Favorov, Alexander V.
    Afsari, Bahman
    Goff, Loyal A.
    Fertig, Elana J.
    CANCER RESEARCH, 2019, 79 (19) : 5102 - 5112
  • [48] Supervised learning of high-confidence phenotypic subpopulations from single-cell data
    Tao Ren
    Canping Chen
    Alexey V. Danilov
    Susan Liu
    Xiangnan Guan
    Shunyi Du
    Xiwei Wu
    Mara H. Sherman
    Paul T. Spellman
    Lisa M. Coussens
    Andrew C. Adey
    Gordon B. Mills
    Ling-Yun Wu
    Zheng Xia
    Nature Machine Intelligence, 2023, 5 : 528 - 541
  • [49] Supervised learning of high-confidence phenotypic subpopulations from single-cell data
    Ren, Tao
    Chen, Canping
    Danilov, Alexey V.
    Liu, Susan
    Guan, Xiangnan
    Du, Shunyi
    Wu, Xiwei
    Sherman, Mara H.
    Spellman, Paul T.
    Coussens, Lisa M.
    Adey, Andrew C.
    Mills, Gordon B.
    Wu, Ling-Yun
    Xia, Zheng
    NATURE MACHINE INTELLIGENCE, 2023, 5 (05) : 528 - +
  • [50] Single-Cell Sequencing of Hepatocellular Carcinoma Reveals Cell Interactions and Cell Heterogeneity in the Microenvironment
    Li, Xinyao
    Wang, Lei
    Wang, Liusong
    Feng, Zanjie
    Peng, Cijun
    INTERNATIONAL JOURNAL OF GENERAL MEDICINE, 2021, 14 : 10141 - 10153
12345