SCENIC+ is a python package to build gene regulatory networks (GRNs) using combined or separate single-cell gene expression (scRNA-seq) and single-cell chromatin accessibility (scATAC-seq) data.
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Question regarding the r2g/tf2g importance scores #67
If I understand the GENIE3/GRNboost algorithms correctly, we first we first normalize the variance per target to 1, such that the importance scores per target sum up to 1 (given that the prediction is almost perfect) which facilitates the comparison of importances score for different target genes.
Why do the importances scores per gene sum up to 1 in the region-gene data frame, but not in the tf-gene data frame?
This is for example how the sum of importances scores per gene looks like
If I understand the GENIE3/GRNboost algorithms correctly, we first we first normalize the variance per target to 1, such that the importance scores per target sum up to 1 (given that the prediction is almost perfect) which facilitates the comparison of importances score for different target genes.
Why do the importances scores per gene sum up to 1 in the region-gene data frame, but not in the tf-gene data frame?
This is for example how the sum of importances scores per gene looks like