Not so good, my expected missense mutation is not significant with this method.
Do you think the idea of VEST is too simple? just use Random Forest and run a machine learning?
The Variant Effect Scoring Tool (VEST) is a new method for prioritizing missense mutations that alter protein activ- ity. VEST uses a supervised machine learning algorithm, Random Forest [22,23], to identify likely functional mis- sense mutations. The training set is a positive class of mis- sense variants from the Human Gene Mutation Database and a negative class of common missense variants detected in the Exome Sequencing Project (ESP) population.