Removal of adata preprocessing #3
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Hi, I'm currently working on improving GPcounts and found that removal of
sc.pp.log1p(adata)would result in better model performance. This is especially true for lower sigma values and could be possibly due to the logarithm decreasing the dispersion of the counts that are sampled from poisson distribution.Additionally, we noticed a bug when generating scales for the use of GPcounts. When setting the family parameter of
smf.glm()it should be set tosm.families.NegativeBinomial(sm.families.links.identity())).fit()instead ofsm.families.NegativeBinomial(sm.families.links.log())).fit(). This fixes the previous errors where most real data counts could not be fitted.These changes have been edited in the fork accompanying this pull request. I eagerly await for your response.