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快速而准确的核心外PCA框架用于大规模的生物库数据

Zilong Li1, Jonas Meisner2,3, Anders Albrechtsen4

  • 1Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, 2200 København, Denmark; zilong.dk@gmail.com aalbrechtsen@bio.ku.dk.

Genome research
|August 24, 2023
PubMed
概括

一个新的工具PCAone加速了大型数据集的主要组件分析 (PCA),使用随机奇数值分解 (RSVD). 它为基因组学和单细胞RNA测序数据提供了更快的计算和内存效率.

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