SuSiE PCA: A scalable Bayesian variable selection technique for principal component analysis

• Published in: iScience Vol. 26; no. 11; p. 108181
• Main Authors: Yuan, Dong, Mancuso, Nicholas
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 17.11.2023; Elsevier
• Subjects: Algorithms; Biocomputational method; Classification of bioinformatical subject; data processing in systems biology; data processing in systems biology; Algorithms; Classification of bioinformatical subject; Biocomputational method

Latent factor models, like principal component analysis (PCA), provide a statistical framework to infer low-rank representation in various biological contexts. However, feature selection is challenging when this low-rank structure manifests from a sparse subspace. We introduce SuSiE PCA, a scalable...