Volume-Regularized Structured Matrix Factorization R package vrnmf version 1.0.2 Implements a set of routines to perform structured matrix factorization with minimum volume constraints. The NMF procedure decomposes a matrix X into a product C * D. Given conditions such that the matrix C is non-negative and has sufficiently spread columns, then volume minimization of a matrix D delivers a correct and unique, up to a scale and permutation, solution (C, D). This package provides both an implementation of volume-regularized NMF and "anchor-free" NMF, whereby the standard NMF problem is reformulated in the covariance domain. This algorithm was applied in Vladimir B. Seplyarskiy Ruslan A. Soldatov, et al. "Population sequencing data reveal a compendium of mutational processes in the human germ line". Science, 12 Aug 2021. <doi:10.1126/science.aba7408>. This package interacts with data available through the 'simulatedNMF' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/vrnmf>. The size of the 'simulatedNMF' package is approximately 8 MB. Software Depends: R (>= 3.5.1) Imports: graphics, ica (>= 1.0), lpSolveAPI (>= 5.5.2.0), Matrix, nnls, parallel (>= 3.5.1), quadprog (>= 1.5), stats Suggests: knitr (>= 1.28), rmarkdown (>= 2.1), testthat Evan Biederstedt <evan.biederstedt@gmail.com> Comprehensive R Archive Network (CRAN) Ruslan Soldatov [aut], Peter Kharchenko [aut], Viktor Petukhov [aut], Evan Biederstedt [cre, aut] GPL-3 2022-02-25 application/tgz https://CRAN.R-project.org/package=vrnmf doi:10.32614/CRAN.package.vrnmf