Comments (2)
ccruizm
commented on July 26, 2024
This was working in the previous version (before the name change to scSpectra). I want to use this new version since it seems there are some new implementations since the last time I tested it :)
Why does the new version of the package not support use_cell_types=False when using GPU?
Would it be an option to assign all cells to a cell type and run it as if they are labeled?
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wallet-maker
commented on July 26, 2024
Hi Cristian, sorry for the delayed response. We are still working on the GPU version. I think your workaround should do. To be safe I recommend you only use global gene sets if you set all cells to one cell type.
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Related Issues (20)
- Example notebook is missing HOT 2
- GPU implementation HOT 16
- train() got an unexpected keyword argument 'label_factors' HOT 2
- spc.est_spectra stalls and go to next step after some epochs
- Unexpected spectra factors and some misc questions HOT 6
- Util function improvements HOT 1
- TypeError: SPECTRA_Model.train() got an unexpected keyword argument 'label_factors' HOT 1
- issue with self.rho = nn.ParameterDict(self.rho) HOT 2
- unbound local variable is_global HOT 1
- UnboundLocalError: local variable 'is_global' referenced before assignment HOT 2
- Number of cores allocation HOT 1
- GPU tutorial? HOT 2
- Running Spectra with mouse data? HOT 1
- Does Spectra accept processed expression matrix as the input? HOT 1
- The meaning of gene weight? HOT 1
- Computing factor importance scores
- Specific factors vary based on global. HOT 1
- run adata.uns['SPECTRA_overlap'].index, and there are some factors without name? HOT 1
- factor importance and information scores
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