NNMF_from_file: Nonnegative matrix factorization
In KSheu/ksheu.lib: KSheu Library1

Input: matrix A (ex. rows as genes, cols as samples) Output: writes to file decomposed matrices W (loadings) and H (scores) that minimize the loss between the original and decomposed matrices

1 2	NNMF_from_file(file, rank = 5, method = "scd", loss = "mkl", impute = F, verbose = 2)

`file`	file for A matrix (.txt or .RDS file)
`rank`	rank for the decompostiton
`method`	'scd' (seq. coord-wise descent) or 'lee' (Lee's algo)
`loss`	'mse' (mean squared error) or 'mkl' (mean KL divergence) for sc data probably better to use KL divergence? (Frobenius norm is standard)
`impute`	default=F Simple NNMF or impute 0 values by first setting them all to NA
`verbose`	0-2