OnlinePCA.jl: A Julia Package for Out-of-core and Sparse Principal Component Analysis

Peer-reviewed software and manuscript. See the JOSS review issue for details: https://github.com/openjournals/joss-reviews/issues/9343 Principal Component Analysis (PCA) is a widely used dimensionality reduction technique, but becomes computationally prohibitive for large data matrices. Recent advances in single-cell omics have led to datasets with millions of cells, for which standard PCA implementations often fail to scale. OnlinePCA.jl is a Julia package that addresses this challenge by providing scalable PCA algorithms (https://github.com/rikenbit/OnlinePCA.jl). Zenodo doi: 10.5281/zenodo.18250632

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