Quantification of cell identity from single-cell gene expression profiles.

Abstract:

:The definition of cell identity is a central problem in biology. While single-cell RNA-seq provides a wealth of information regarding cell states, better methods are needed to map their identity, especially during developmental transitions. Here, we use repositories of cell type-specific transcriptomes to quantify identities from single-cell RNA-seq profiles, accurately classifying cells from Arabidopsis root tips and human glioblastoma tumors. We apply our approach to single cells captured from regenerating roots following tip excision. Our technique exposes a previously uncharacterized transient collapse of identity distant from the injury site, demonstrating the biological relevance of a quantitative cell identity index.

journal_name

Genome Biol

journal_title

Genome biology

authors

Efroni I,Ip PL,Nawy T,Mello A,Birnbaum KD

doi

10.1186/s13059-015-0580-x

subject

Has Abstract

pub_date

2015-01-22 00:00:00

pages

9

eissn

1474-7596

issn

1474-760X

pii

s13059-015-0580-x

journal_volume

16

pub_type

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