Predict gene-level expression given sequences

Feedback & Feature Requests
4

Hi,

I tested the model.score_interval and compared its predictions with those from model.score_variant.
I found that the correlation between the two outputs is quite high (~0.98), which is great, but the absolute values differ substantially for highly expressed genes.

  1. Why could this difference occur, especially for genes with high predicted expression?

  2. Also, could someone clarify what the width parameter in GeneMaskScorer actually means in practice?

I’ve read this thread, but the explanation there (“The width of the target interval to include in the aggregation”) is still not fully clear to me — does it define the window size around the gene body used for aggregation, or something else?

Thanks in advance!