Performs L1 normalization on input data such that the sum of expression values for each cell sums to 1, then returns normalized matrix to the metric space using median UMI count per cell effectively scaling all cells as if they were sampled evenly.
library.size.normalize(data, verbose = FALSE)
matrix (n_samples, n_dimensions) 2 dimensional input data array with n cells and p dimensions
boolean, default=FALSE. If true, print verbose output
data_norm matrix (n_samples, n_dimensions) 2 dimensional array with normalized gene expression values