Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge

MOTIVATION: Single cell RNA-seq (scRNA-seq) data contains a wealth of information which has to be inferred computationally from the observed sequencing reads. As the ability to sequence more cells improves rapidly, existing computational tools suffer from three problems. (i) The decreased reads-per-...

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Detalles Bibliográficos
Autores principales: Mukherjee, Sumit, Zhang, Yue, Fan, Joshua, Seelig, Georg, Kannan, Sreeram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Ismb 2018–Intelligent Systems for Molecular Biology Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022691/
https://www.ncbi.nlm.nih.gov/pubmed/29949988
http://dx.doi.org/10.1093/bioinformatics/bty293

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022691/
https://www.ncbi.nlm.nih.gov/pubmed/29949988
http://dx.doi.org/10.1093/bioinformatics/bty293

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