Benchmarking principal component analysis for large-scale single-cell RNA-sequencing

BACKGROUND: Principal component analysis (PCA) is an essential method for analyzing single-cell RNA-seq (scRNA-seq) datasets, but for large-scale scRNA-seq datasets, computation time is long and consumes large amounts of memory. RESULTS: In this work, we review the existing fast and memory-efficient...

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Detalles Bibliográficos
Autores principales: Tsuyuzaki, Koki, Sato, Hiroyuki, Sato, Kenta, Nikaido, Itoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6970290/
https://www.ncbi.nlm.nih.gov/pubmed/31955711
http://dx.doi.org/10.1186/s13059-019-1900-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6970290/
https://www.ncbi.nlm.nih.gov/pubmed/31955711
http://dx.doi.org/10.1186/s13059-019-1900-3

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