volnmf_procrustes

<p>Numeric Matrices. Orthonormal transformation convert matrix <code>B</code> in matrix <code>A</code>.</p>

<p><code>volnmf_procrustes</code> finds orthonormal matrix <code>Q</code> that minimizes objective
<code>||A-B*Q||^2</code></p>

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.

Evan Biederstedt

vrnmf

Volume-Regularized Structured Matrix Factorization

volnmf_procrustes: Procrustes algorithm estimates orthonormal transformation between two matrices.

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