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I optimized my single cell data of 13 cell types and found highly correlated cell types. I ran the optimization on those cell types thus adding 10 more genes to the signature matrix- I am not sure how to deconvolute the bulk data now. I was trying something along these lines: [ag.AutoGeneS(data=signature_matrix_np), ag.deconvolve(numeric_bulk.T, model='nusvr')] but the ag is picking up vales from the new optimization which is on 2 cell types only..
The text was updated successfully, but these errors were encountered:
Thanks for your interest.
The anndata will be stored in the model when you initiate it which in your case has been the latest anndata you trained the model with.
I would suggest to use init function again using your original data. But have in mind that you should feed in your integrated list of genes (concatenating the genes from the data with 13 cell types and the genes from the data with only 2 cell types) to the deconvolution function.
You should use key in deconvolve function for that.
Let me know if this solves the problem.
Best,
Hana
Hi Hana,
Do you have a documentation for AutoGeneS+?
I optimized my single cell data of 13 cell types and found highly correlated cell types. I ran the optimization on those cell types thus adding 10 more genes to the signature matrix- I am not sure how to deconvolute the bulk data now. I was trying something along these lines: [ag.AutoGeneS(data=signature_matrix_np), ag.deconvolve(numeric_bulk.T, model='nusvr')] but the ag is picking up vales from the new optimization which is on 2 cell types only..
The text was updated successfully, but these errors were encountered: