Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 2041-1723

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases ; volume:9 ; number:1 ; day:9 ; month:11 ; year:2018 ; pages:1-8 ; date:12.2018
Nature Communications ; 9, Heft 1 (9.11.2018), 1-8, 12.2018

Creator: Vallania, Francesco
Tam, Andrew
Lofgren, Shane
Schaffert, Steven
Azad, Tej D.
Bongen, Erika
Haynes, Winston
Alsup, Meia
Alonso, Michael
Davis, Mark
Engleman, Edgar
Khatri, Purvesh

Contributor: SpringerLink (Online service)

DOI: 10.1038/s41467-018-07242-6

URN: urn:nbn:de:101:1-2018122321302038392406

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:47 AM CEST

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Vallania, Francesco
Tam, Andrew
Lofgren, Shane
Schaffert, Steven
Azad, Tej D.
Bongen, Erika
Haynes, Winston
Alsup, Meia
Alonso, Michael
Davis, Mark
Engleman, Edgar
Khatri, Purvesh
SpringerLink (Online service)

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Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases

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Other Objects (12)

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