Many of our matrices are log normalized, which tends to eliminate
the number of non zero values (if there were any). This prevents
the matrix from being stored as a sparse matrix. The solution here
is to use a simple transformation to make it sparse again. The most
common value from each column is subtracted from that column. These
values that were subtracted are saved in an array called X_col_shift.
The cellxgene code needs to understand how to undo the transformation when
operating over the X matrix.
- added script to create a synthetic dataset for testing
- added a script to convert an existing CXG dataset to a sparse CXG dataset
