Given a data-matrix of numeric data, calculates the rank of each row in each column (feature in sample), gets the median rank across all columns, and returns the original data with missing values set to NA, the reordered data, and a data.frame of the ranks of each feature and the number of missing values.
Usage
rank_order_data(data_matrix, global_na = c(NA, Inf, 0), sample_classes = NULL)