CellTree: An R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data

BMC Bioinformatics

Volumn 17, Issue 1, 2016, Pages

  duVerle, David A ^a,e   Yotsukura, Sohiya ^b   Nomura, Seitaro ^c   Aburatani, Hiroyuki ^c   Tsuda, Koji ^a,d,e  

^a UNIVERSITY OF TOKYO   (Japan)

^b KYOTO UNIVERSITY   (Japan)

^c UNIVERSITY OF TOKYO   (Japan)

^d NATIONAL INSTITUTE FOR MATERIALS SCIENCE   (Japan)

^e NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

Author keywords

Cell differentiation; Cell heterogeneity; Human stem cell; Single cell RNA seq

Indexed keywords

BIOINFORMATICS; CELL CULTURE; CELL PROLIFERATION; CELLS; GENE EXPRESSION; GENES; POPULATION STATISTICS; RNA; STEM CELLS; TREES (MATHEMATICS);

BIOLOGICAL INSIGHT; CELL DIFFERENTIATION; DIMENSIONALITY REDUCTION TECHNIQUES; DOCUMENT ANALYSIS; EXPRESSION MEASUREMENTS; HIERARCHICAL STRUCTURES; SINGLE CELLS; STATISTICAL APPROACH;

CYTOLOGY;

CELL DIFFERENTIATION; CELL HETEROGENEITY; CELL POPULATION; SOUND; STATISTICAL MODEL; STEM CELL; GENETICS; HUMAN; IMMUNOLOGY; PROCEDURES; SEQUENCE ANALYSIS;

RNA;

CELL DIFFERENTIATION; HUMANS; RNA; SEQUENCE ANALYSIS, RNA; STEM CELLS;

EID: 84987652887     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-1175-6     Document Type: Article

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