Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

Shyam Prabhakar, Paul Robson, Iain Beehuat Tan and colleagues characterize the cellular heterogeneity of colorectal tumors and their microenvironment on the basis of single-cell RNA–seq data analyzed with their newly developed clustering algorithm, reference component analysis (RCA). Their analyses...

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Veröffentlicht in:	Nature genetics 2017-05, Vol.49 (5), p.708-718
Hauptverfasser:	Li, Huipeng, Courtois, Elise T, Sengupta, Debarka, Tan, Yuliana, Chen, Kok Hao, Goh, Jolene Jie Lin, Kong, Say Li, Chua, Clarinda, Hon, Lim Kiat, Tan, Wah Siew, Wong, Mark, Choi, Paul Jongjoon, Wee, Lawrence J K, Hillmer, Axel M, Tan, Iain Beehuat, Robson, Paul, Prabhakar, Shyam
Format:	Artikel
Sprache:	eng
Schlagworte:	13/1 14/19 38/32 38/91 631/114/2164 631/208/212/2019 692/699/67/1504/1885 A549 Cells Aberration Accuracy Agriculture Algorithms Animal Genetics and Genomics Biology Biomedicine Cancer Cancer Research Cell Line Cell Line, Tumor Cluster Analysis Clustering Colon Colorectal cancer Colorectal Neoplasms - genetics Colorectal Neoplasms - pathology Epithelial-Mesenchymal Transition - genetics Fibroblasts Fibroblasts - metabolism Gene expression Gene Expression Profiling - methods Gene Expression Regulation, Neoplastic Gene Function Genetic Heterogeneity Genomes Genomics Heterogeneity Human Genetics Humans Immunohistochemistry In Situ Hybridization, Fluorescence K562 Cells Laboratories Metastasis Methods Microenvironments Principal Component Analysis Prognosis Quality control Ribonucleic acid RNA Rodents Sequence Analysis, RNA - methods Single-Cell Analysis - methods Stem cells Studies Subgroups Survival Analysis Transcriptome Tumors
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