Show simple item record

dc.contributor.author
He, Zhisong
dc.contributor.author
Brazovskaja, Agnieska
dc.contributor.author
Ebert, Sebastian
dc.contributor.author
Camp, J. Gray
dc.contributor.author
Treutlein, Barbara
dc.date.accessioned
2020-09-09T08:12:04Z
dc.date.available
2020-09-09T03:12:16Z
dc.date.available
2020-09-09T08:12:04Z
dc.date.issued
2020
dc.identifier.issn
1474-760X
dc.identifier.other
10.1186/s13059-020-02147-4
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/439181
dc.identifier.doi
10.3929/ethz-b-000439181
dc.description.abstract
It is a major challenge to integrate single-cell sequencing data across experiments, conditions, batches, time points, and other technical considerations. New computational methods are required that can integrate samples while simultaneously preserving biological information. Here, we propose an unsupervised reference-free data representation, cluster similarity spectrum (CSS), where each cell is represented by its similarities to clusters independently identified across samples. We show that CSS can be used to assess cellular heterogeneity and enable reconstruction of differentiation trajectories from cerebral organoid and other single-cell transcriptomic data, and to integrate data across experimental conditions and human individuals.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
CSS: cluster similarity spectrum integration of single-cell genomics data
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2020-09-01
ethz.journal.title
Genome Biology
ethz.journal.volume
21
en_US
ethz.journal.issue
1
en_US
ethz.journal.abbreviated
Genome Biol
ethz.pages.start
224
en_US
ethz.size
21 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::09485 - Treutlein, Barbara / Treutlein, Barbara
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::09485 - Treutlein, Barbara / Treutlein, Barbara
ethz.date.deposited
2020-09-09T03:12:20Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-09-09T08:12:16Z
ethz.rosetta.lastUpdated
2024-02-02T12:00:17Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=CSS:%20cluster%20similarity%20spectrum%20integration%20of%20single-cell%20genomics%20data&rft.jtitle=Genome%20Biology&rft.date=2020&rft.volume=21&rft.issue=1&rft.spage=224&rft.issn=1474-760X&rft.au=He,%20Zhisong&Brazovskaja,%20Agnieska&Ebert,%20Sebastian&Camp,%20J.%20Gray&Treutlein,%20Barbara&rft.genre=article&rft_id=info:doi/10.1186/s13059-020-02147-4&
 Search print copy at ETH Library

Files in this item

Thumbnail

Publication type

Show simple item record