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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...
Autores principales: | Tsuyuzaki, Koki, Sato, Hiroyuki, Sato, Kenta, Nikaido, Itoshi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
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 |
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