It's mentioned in the paper that scDblFinder utilizes multiple features obtained from the Knn network, such as projections on principal components; library size; the number of detected features; and co-expression scores. But I can only find the scDblFinder.weighted and scDblFinder.cxds_score in the output R object. Could you tell me how to obtain all features used in training GDBT tree in the R object?
Hi scDblFinder team!
It's mentioned in the paper that scDblFinder utilizes multiple features obtained from the Knn network, such as projections on principal components; library size; the number of detected features; and co-expression scores. But I can only find the scDblFinder.weighted and scDblFinder.cxds_score in the output R object. Could you tell me how to obtain all features used in training GDBT tree in the R object?
Thanks