MOFA+ Multi-Omics Factor Analysis
Overview
MOFA+ (Multi-Omics Factor Analysis v2) is an unsupervised statistical framework that jointly decomposes multiple omics datasets into a small set of latent factors. Each factor captures an independent source of variation (e.g., cell cycle, a disease phenotype, a technical batch) and is associated with feature weights (loadings) that reveal which genes, peaks, or proteins drive it. The Python package mofapy2 produces an HDF5 model file compatible
[Description truncada. Veja o README completo no GitHub.]