Is it possible to adjust the priors so that cellbender can work with shallow-sequenced data?

[onurcanbektas]

Is it possible to adjust the priors so that cellbender can work with shallow-sequenced data?

At the moment, possibly because of the fewer number of counts in droplet, it is giving me this error in a shallow-sequnced data:

cellbender:remove-background: CellBender 0.3.0
cellbender:remove-background: (Workflow hash 84b52a7a4f)
cellbender:remove-background: 2024-03-24 14:01:33
cellbender:remove-background: Running remove-background
cellbender:remove-background: Loading data from /scratch/o/Onurcan.Bektas/axolotl.rulands.yun/data/230112ITR/cooked/cellranger.gex_only.cellbender//sn188/raw_feature_bc_matrix.h5
cellbender:remove-background: CellRanger v3 format
cellbender:remove-background: WARNING: Only 45938 barcodes in the input file. Ensure this is a raw (unfiltered) file with all barcodes, including the empty droplets.
cellbender:remove-background: Features in dataset: 99102 Gene Expression
cellbender:remove-background: Excluding Peaks features (output will equal input).
cellbender:remove-background: - This results in the exclusion of 0 features.
cellbender:remove-background: Trimming features for inference.
cellbender:remove-background: 17873 features have nonzero counts.
/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/data/priors.py:144: RuntimeWarning: divide by zero encountered in log
cell_counts = np.exp(np.mean(np.log(umi_counts[order][:expected_cells]))).item()
/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/data/priors.py:170: RuntimeWarning: divide by zero encountered in log
cell_counts = np.exp(np.mean(np.log(umi_counts[order][:expected_cells]))).item()
/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/data/priors.py:383: RuntimeWarning: divide by zero encountered in log
log_counts_crossover = (np.log(surely_empty_counts) + np.log(priors['cell_counts'])) / 2
cellbender:remove-background: Prior on counts for cells is 0
cellbender:remove-background: Prior on counts for empty droplets is 0
Traceback (most recent call last):
File "/home/o/Onurcan.Bektas/.local/bin/cellbender", line 8, in
sys.exit(main())
File "/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/base_cli.py", line 118, in main
cli_dict[args.tool].run(args)
File "/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/cli.py", line 185, in run
return main(args)
File "/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/cli.py", line 230, in main
posterior = run_remove_background(args)
File "/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/run.py", line 84, in run_remove_background
dataset_obj = get_dataset_obj(args=args)
File "/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/data/dataset.py", line 526, in get_dataset_obj
return SingleCellRNACountsDataset(
File "/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/data/dataset.py", line 167, in init
self._trim_noiseless_features()
File "/home/o/Onurcan.Bektas/.local/lib/python3.10/site-packages/cellbender/remove_background/data/dataset.py", line 290, in _trim_noiseless_features
mean_counts_per_empty_g = np.array(count_matrix_empties.mean(axis=0)).squeeze()
File "/software/opt/focal/x86_64/python/3.10-2022.08/lib/python3.10/site-packages/scipy/sparse/_base.py", line 1191, in mean
return (inter_self * (1.0 / self.shape[0])).sum(
ZeroDivisionError: float division by zero