Capice: a computational method for consequence-agnostic pathogenicity interpretation of clinical exome variations

HIGHLIGHTS

• who: Shuang Li from the measuring model performance in the neutral benchmark dataset, we examined the false-positive rateThe falsepositive rate is the number of true neutral variants but predicted as pathogenic divided by the number of true neutral variants. To evaluate the robustness of the model predictions, we performed bootstrap on the benchmark dataset for standard deviation measurement for , repetitions, with the same sample size of the benchmark dataset for each repetition [40]. To evaluate performance in solved patients, we used the previously diagnosed patients with clear record of the disease-causing variant from University Medical . . .
  

   

  

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