Efficient integration of heterogeneous single-cell transcriptomes using Scanorama

Nature Biotechnology

Volumn 37, Issue 6, 2019, Pages 685-691

  Hie, Brian ^a   Bryson, Bryan ^b   Berger, Bonnie ^a,c  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b Massachusetts Institute of Technology   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELLS; CYTOLOGY;

BATCH EFFECT; BIOLOGICAL INSIGHT; DIFFERENT STAGES; HETEROGENEOUS COLLECTIONS; ORDERS OF MAGNITUDE; RNA SEQUENCING; TEMPORAL CHANGE; TRANSCRIPTOMES;

DATA INTEGRATION;

TRANSCRIPTOME;

ALGORITHM; ARTICLE; CELL DIFFERENTIATION; CELL LINEAGE; CELLS BY BODY ANATOMY; CONTROLLED STUDY; EMBRYO; HEK293T CELL LINE; HUMAN; HUMAN CELL; JURKAT CELL LINE; MACROPHAGE; NONHUMAN; PRIORITY JOURNAL; RNA SEQUENCE; SINGLE CELL ANALYSIS; SINGLE CELL RNA SEQUENCING; TIME SERIES ANALYSIS; CHEMISTRY; GENE EXPRESSION PROFILING; GENETICS; METABOLISM; MONOCYTE; PROCEDURES; SEQUENCE ANALYSIS;

CELL DIFFERENTIATION; GENE EXPRESSION PROFILING; HUMANS; MACROPHAGES; MONOCYTES; SEQUENCE ANALYSIS, RNA; SINGLE-CELL ANALYSIS; TRANSCRIPTOME;

EID: 85065343062     PISSN: 10870156     EISSN: 15461696     Source Type: Journal    
DOI: 10.1038/s41587-019-0113-3     Document Type: Article

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