Identification of cell types from single-cell transcriptomes using a novel clustering method

Motivation: The recent advance of single-cell technologies has brought new insights into complex biological phenomena. In particular, genome-wide single-cell measurements such as transcriptome sequencing enable the characterization of cellular composition as well as functional variation in homogenic...

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Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2015-06, Vol.31 (12), p.1974-1980
Main Authors: Xu, Chen, Su, Zhengchang
Format: Article
Language:English
Subjects:
Algorithms
Animals
Cell Lineage - genetics
Cluster Analysis
Embryo, Mammalian - cytology
Embryo, Mammalian - metabolism
Gene Expression Regulation
High-Throughput Nucleotide Sequencing - methods
Humans
Mice
Neoplasms - genetics
Original Papers
Programming Languages
Single-Cell Analysis - methods
Transcriptome
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