factor importance and information scores

[bpkwee]

Thanks for the amazing package!

I successfully managed to run spectra on a few datasets and I was eager to calculate the importance and information scores for the factors that spectra found. However, while reading the utils functions it was not immediately clear how to use these functions to calculate the scores for each factor:

1. There is no mention of an importance score function, am I right to assume that this is calculated with the holdout_loss() function? For this function I am unsure what cell_type and labels arguments should contain. The lines below suggest that there should be a loop over each unique cell_type, where labels is an array of the the cell_type annotations for each cell. Am I correct that this loop missing from the current code?
   

   spectra/src/Spectra/Spectra_util.py

   Line 371 in 474a3c7

   # loop through cell types and evaluate loss at every cell type

   spectra/src/Spectra/Spectra_util.py

   Line 382 in 474a3c7

   X_c = X[labels == cell_type]

2. The get_information_score returns and empty list because of the commented out code. In here the labels parameter is missing as mentioned in the #todo

   spectra/src/Spectra/Spectra_util.py

   Line 428 in 474a3c7

   # TODO: Fix undefined "labels" variable

   Islabels the supposed to contain the same array of cell_type annotations as in holdout_loss()?

In #24 (comment) it is mentioned that an example would be added to the tutorial, but I have not found it there. Ideally I would like to make a figure similar to "Extended Data Fig. 6a".

Any help would be greatly appreciated.

[CorinnaLo]

Hello,
I'm also trying to apply Spectra to my data at the moment and was having the same question and wondering how to derive the importance scores.
@bpkwee did you already find a solution for this.

[bpkwee]

@CorinnaLo no, unfortunately not yet...

[CorinnaLo]

@russellkune for using Spectra which seems to be a very cool method it would be very helpful for me if you and/or one of the other developers could maybe provide some insights on how to calculate the factor importance and information scores based on the model output.
Thanks a lot!