scROSHI: robust supervised hierarchical identification of single cells

Identifying cell types based on expression profiles is a pillar of single cell analysis. Existing machine-learning methods identify predictive features from annotated training data, which are often not available in early-stage studies. This can lead to overfitting and inferior performance when appli...

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Detalles Bibliográficos
Autores principales: Prummer, Michael, Bertolini, Anne, Bosshard, Lars, Barkmann, Florian, Yates, Josephine, Boeva, Valentina, Stekhoven, Daniel, Singer, Franziska
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Methods Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10273189/
https://www.ncbi.nlm.nih.gov/pubmed/37332656
http://dx.doi.org/10.1093/nargab/lqad058

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10273189/
https://www.ncbi.nlm.nih.gov/pubmed/37332656
http://dx.doi.org/10.1093/nargab/lqad058

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