A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing

Single-cell genomics is rapidly advancing our knowledge of the diversity of cell phenotypes, including both cell types and cell states. Driven by single-cell/-nucleus RNA sequencing (scRNA-seq), comprehensive cell atlas projects characterizing a wide range of organisms and tissues are currently unde...

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Detalles Bibliográficos
Autores principales: Aevermann, Brian, Zhang, Yun, Novotny, Mark, Keshk, Mohamed, Bakken, Trygve, Miller, Jeremy, Hodge, Rebecca, Lelieveldt, Boudewijn, Lein, Ed, Scheuermann, Richard H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2021
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494219/
https://www.ncbi.nlm.nih.gov/pubmed/34088715
http://dx.doi.org/10.1101/gr.275569.121

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494219/
https://www.ncbi.nlm.nih.gov/pubmed/34088715
http://dx.doi.org/10.1101/gr.275569.121

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