nmf_unfolded: Computes non-negative matrix factorization on the tensor...

In scITD: Single-Cell Interpretable Tensor Decomposition

Computes non-negative matrix factorization on the tensor unfolded along the donor dimension

Description

Computes non-negative matrix factorization on the tensor unfolded along the donor dimension

Usage

nmf_unfolded(container, ranks)

Arguments

container	environment Project container that stores sub-containers for each cell type as well as results and plots from all analyses
ranks	numeric The number of factors to extract. Unlike with the Tucker decomposition, this should be a single number.

Value

The project container with results of the decomposition in container$tucker_results. The results object is a list with the donor scores matrix in the first element and the unfolded loadings matrix in the second element.

Examples

test_container <- nmf_unfolded(test_container, 2)

scITD documentation built on Sept. 8, 2023, 5:11 p.m.