Hello,
I am analyzing variant effects using AlphaGenome and I have a question about how to interpret the visualization results.
When I plot the predictions for REF and ALT sequences, the curves often appear visually overlapping in the figure. However, when I compute the numerical difference (ALT − REF), there is a non-zero effect.
For example:
max_delta = 8
In addition, the results from the variant scoring step show both a high raw_score and a high quantile_score.
In my analysis I also filtered variants using a quantile_score threshold above 0.9 (a threshold defined for my study). However, even among these variants with high quantile_score and high raw_score, the RNA-seq plots sometimes still look almost identical.
This raises a few questions:
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Is it expected that REF and ALT tracks may appear visually identical even for variants with high raw_score and quantile_score (>0.9)?
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In other words, can a variant have a high predicted impact according to the scoring metrics, but still produce changes that are difficult to visually detect in the RNA-seq plots?
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Should interpretation of the variant effect rely mainly on the raw_score (or aggregated score) rather than the visual difference in the plotted tracks?
My understanding is that the quantile_score represents the rank of the raw_score relative to a background distribution of common variants, indicating how extreme the predicted effect is, rather than how large the visual difference in the track should appear.
I would appreciate any clarification on how to interpret this situation.
Thank you!
