vrnmf: Volume-Regularized Structured Matrix Factorization

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.

Version: 1.0.0
Depends: R (≥ 3.5.1)
Imports: graphics, ica (≥ 1.0), lpSolveAPI (≥ 5.5.2.0), nnls, parallel (≥ 3.5.1), quadprog (≥ 1.5), stats
Suggests: knitr (≥ 1.28), rmarkdown (≥ 2.1), testthat
Published: 2021-08-20
Author: Ruslan Soldatov [aut], Peter Kharchenko [aut], Evan Biederstedt [cre, aut]
Maintainer: Evan Biederstedt <evan.biederstedt at gmail.com>
BugReports: https://github.com/kharchenkolab/vrnmf/issues
License: GPL-3
URL: https://github.com/kharchenkolab/vrnmf
NeedsCompilation: no
Materials: README
CRAN checks: vrnmf results

Documentation:

Reference manual: vrnmf.pdf

Downloads:

Package source: vrnmf_1.0.0.tar.gz
Windows binaries: r-devel: vrnmf_1.0.0.zip, r-release: vrnmf_1.0.0.zip, r-oldrel: vrnmf_1.0.0.zip
macOS binaries: r-release (arm64): vrnmf_1.0.0.tgz, r-release (x86_64): vrnmf_1.0.0.tgz, r-oldrel: vrnmf_1.0.0.tgz

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