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Reworked into a tree format where it iterates the rows to form cells (~1k iter/s), and then iterate through the cells (~150 iter/s) compared to previous 3-4 iter/s.
Adjusted small bug where the duplicate_counts were not adding up
Refactored Query.
Now does the __init__ method preloads the required fields as a tree and a separate retrieve method and access the dictionaries much faster. Same method as above.
read_10x_vdj
Refactored parse_annotation which was slowing everything down.
Similar method to above
sanitize_data
Use airr.RearrangementSchema to match the dtype to deal with missing values. Also speed up some steps to make the validation faster.
Also bug fix causing float columns to be unintentially converted to integers e.g. mu_freq columns should hopefully now return properly.
Added write_airr function that basically calls airr.create_rearrangement
Adjusted quantify_mutations to hopefully return the right dtypes now.
Added option to filter_contigs to run without anndata.
Bug fix to dandelion_preprocessing.py to let it run quantify_mutations based on the args.file_prefix.