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 Bioljournal_title
Genome biologyauthors
Efroni I,Ip PL,Nawy T,Mello A,Birnbaum KDdoi
10.1186/s13059-015-0580-xsubject
Has Abstractpub_date
2015-01-22 00:00:00pages
9eissn
1474-7596issn
1474-760Xpii
s13059-015-0580-xjournal_volume
16pub_type
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