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overview [2012/02/15 12:20]
ivan [Sequence-based features]
overview [2017/03/10 12:56] (current)
ivan [Prediction]
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 For a mutation, PolyPhen-2 calculates Naïve Bayes posterior probability that this mutation is damaging and reports estimates of false positive rate (FPR, the chance that the mutation is classified as damaging when it is in fact non-damaging) and true positive rate (TPR, the chance that the mutation is classified as damaging when it is indeed damaging). A mutation is also appraised qualitatively, as **benign**, **possibly damaging**, or **probably damaging** based on pairs of false positive rate (FPR) thresholds, optimized separately for each model (e.g., HumDiv and HumVar). For a mutation, PolyPhen-2 calculates Naïve Bayes posterior probability that this mutation is damaging and reports estimates of false positive rate (FPR, the chance that the mutation is classified as damaging when it is in fact non-damaging) and true positive rate (TPR, the chance that the mutation is classified as damaging when it is indeed damaging). A mutation is also appraised qualitatively, as **benign**, **possibly damaging**, or **probably damaging** based on pairs of false positive rate (FPR) thresholds, optimized separately for each model (e.g., HumDiv and HumVar).
  
-Current version 2.1.0 of the PolyPhen-2 uses 5% / 10% FPR for **HumDiv** model and 10% / 20% FPR for **HumVar** model as the thresholds for this ternary classification. Mutations with their posterior probability scores associated with estimated false positive rates at or below the first (lower) FPR value are predicted to be **probably damaging** (more confident prediction). Mutations with the posterior probabilities associated with false positive rates at or below the second (higher) FPR value are predicted to be **possibly damaging** (less confident prediction). Mutations with estimated false positive rates above the second (higer) FPR value are classified as **benign**.+Current version 2.of the PolyPhen-2 uses 5% / 10% FPR for **HumDiv** model and 10% / 20% FPR for **HumVar** model as the thresholds for this ternary classification. Mutations with their posterior probability scores associated with estimated false positive rates at or below the first (lower) FPR value are predicted to be **probably damaging** (more confident prediction). Mutations with the posterior probabilities associated with false positive rates at or below the second (higher) FPR value are predicted to be **possibly damaging** (less confident prediction). Mutations with estimated false positive rates above the second (higer) FPR value are classified as **benign**.
  
 If the lack of data does not allow to make a prediction then the outcome is reported as **unknown**. If the lack of data does not allow to make a prediction then the outcome is reported as **unknown**.
  
   
 
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