Work

FastPCA: An R package for fast singular value decomposition

Year: 2026

Type: article

Abstract: The FastPCA package provides an interface to optimized matrix multiplication libraries (libtorch) for the purpose of singular value decomposition.Using FastPCA to perform randomized singular value decomposition (SVD, (Halko, Martinsson, & Tropp, 2011)) with the torch or pytorch backend drastically reduces the computational time compared to base R prcomp and other truncated singular value decomposition.Developed for biological data such as single-cell RNA-sequencing, spatial transcriptomics, or matrix-assisted laser desorption/ionization (MALDI imaging), FastPCA can efficiently and accurately identify the leading singular values in high-dimensional data.

Source: The Journal of Open Source Software

DOI: 10.21105/joss.09706

Authors: Kimberly R. Ward, Mitchell Hayes, Lauren C Peres, Brooke L Fridley, Steven Eschrich, Alex C Soupir

Institutions: Moffitt Cancer Center, University of Missouri–Kansas City

Language: English

Topic: Data Analysis with R

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: National Institutes of Health, National Cancer Institute

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