Deep single-cell RNA-seq data clustering with graph prototypical contrastive learning

MOTIVATION: Single-cell RNA sequencing enables researchers to study cellular heterogeneity at single-cell level. To this end, identifying cell types of cells with clustering techniques becomes an important task for downstream analysis. However, challenges of scRNA-seq data such as pervasive dropout...

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Detalles Bibliográficos
Autores principales: Lee, Junseok, Kim, Sungwon, Hyun, Dongmin, Lee, Namkyeong, Kim, Yejin, Park, Chanyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246584/
https://www.ncbi.nlm.nih.gov/pubmed/37233193
http://dx.doi.org/10.1093/bioinformatics/btad342

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246584/
https://www.ncbi.nlm.nih.gov/pubmed/37233193
http://dx.doi.org/10.1093/bioinformatics/btad342

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