MOFA2

MOFA is a factor analysis model that provides a general framework for the integration of multi-omic data sets in an unsupervised fashion. Intuitively, MOFA can be viewed as a versatile and statistically rigorous generalization of principal component analysis to multi-omics data. Given several data matrices with measurements of multiple -omics data types on the same or on overlapping sets of samples, MOFA infers an interpretable low-dimensional representation in terms of a few latent factors. These learnt factors represent the driving sources of variation across data modalities, thus facilitating the identification of cellular states or disease subgroups.

homepage: https://cran.r-project.org/web/packages/rhandsontable/index.html

version	versionsuffix	toolchain
1.14.0	-R-4.3.2	foss/2023a

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