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Hi, how to calibrate bonito trained models so base qualities correspond to expected error rate? For example config.toml for RNA004 sup models uses:
config.toml
[qscore] scale = 0.9 bias = -0.1
How were those values obtained?
The text was updated successfully, but these errors were encountered:
any update on this? we're in the review process of basecalling model trained with bonito and we are unable to calibrate qscores therefore qscores from CTC-CRF models are not comparable with older models (flip-flop). I have opened similar issue in dorado repo
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I see your paper is accepted https://pubmed.ncbi.nlm.nih.gov/39271295/ Congrats, did you figure it out at the end? Thanks
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Hi, how to calibrate bonito trained models so base qualities correspond to expected error rate?
For example
config.toml
for RNA004 sup models uses:How were those values obtained?
The text was updated successfully, but these errors were encountered: