Cell type prioritization in single-cell data

We present Augur, a method to prioritize the cell types most responsive to biological perturbations in single-cell data. Augur employs machine-learning framework to quantify the separability of perturbed and unperturbed cells within a high-dimensional space. We validate our method on single-cell RNA...

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Publicado en:Nat Biotechnol
Autores principales: Skinnider, Michael A., Squair, Jordan W., Kathe, Claudia, Anderson, Mark A., Gautier, Matthieu, Matson, Kaya J.E., Milano, Marco, Hutson, Thomas H., Barraud, Quentin, Phillips, Aaron A., Foster, Leonard J., La Manno, Gioele, Levine, Ariel J., Courtine, Grégoire
Formato: Artigo
Lenguaje:Inglês
Publicado: 2021
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Article
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC7610525/
https://ncbi.nlm.nih.gov/pubmed/32690972
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41587-020-0605-1
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