Deep learning–based cell composition analysis from tissue expression profiles

We present Scaden, a deep neural network for cell deconvolution that uses gene expression information to infer the cellular composition of tissues. Scaden is trained on single-cell RNA sequencing (RNA-seq) data to engineer discriminative features that confer robustness to bias and noise, making comp...

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Detalles Bibliográficos
Autores principales: Menden, Kevin, Marouf, Mohamed, Oller, Sergio, Dalmia, Anupriya, Magruder, Daniel Sumner, Kloiber, Karin, Heutink, Peter, Bonn, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2020
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439569/
https://www.ncbi.nlm.nih.gov/pubmed/32832661
http://dx.doi.org/10.1126/sciadv.aba2619

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439569/
https://www.ncbi.nlm.nih.gov/pubmed/32832661
http://dx.doi.org/10.1126/sciadv.aba2619

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