Hi! Thanks for your method, and congratulations on the publication!
I am developing a toolbox for patient-level analysis of single-cell data called patpy. It contains an interface to patient representation and patient-level prediction methods. PaSCient fits perfectly into it (and seems to work really well!), so I decided to integrate it into patpy. Could you please take a look at the PR?
I would recommend checking 2 things:
- PaSCient interface at
src/patpy/tl/supervised.py
- Example notebook at
docs/notebooks/supervised_methods_example.ipynb
Score-wise, paSCient performs really well, but I have some concerns regarding cell importance scores. They do not look as clean as in the paper. Please feel free to commit to the PR or comment on it.
Thanks again! Hope more people will see your amazing method via patpy
Hi! Thanks for your method, and congratulations on the publication!
I am developing a toolbox for patient-level analysis of single-cell data called patpy. It contains an interface to patient representation and patient-level prediction methods. PaSCient fits perfectly into it (and seems to work really well!), so I decided to integrate it into patpy. Could you please take a look at the PR?
I would recommend checking 2 things:
src/patpy/tl/supervised.pydocs/notebooks/supervised_methods_example.ipynbScore-wise, paSCient performs really well, but I have some concerns regarding cell importance scores. They do not look as clean as in the paper. Please feel free to commit to the PR or comment on it.
Thanks again! Hope more people will see your amazing method via patpy