fathmm

Functional Analysis through Hidden Markov Models (v2.3)

A high-throughput web-server capable of predicting the functional consequences of both coding variants, i.e. non-synonymous single nucleotide variants (nsSNVs), and non-coding variants in the human genome.

Inherited Disease Use this option to return predictions capable of discriminating between disease-causing mutations and neutral polymorphisms.
Cancer Use this option to return predictions capable of distinguishing between cancer-promoting/driver mutations and other germline polymorphisms
Disease-Specific Use this option to return a list of ranked variants that are potentially functionally relevant to to your disease of interest.
FATHMM-MKL Our MKL algorithm integrates functional annotations from ENCODE with nucleotide-based HMMs. Use this option to return predictions on both coding and non-coding variants.
FATHMM-XF Our XF algorithm incorporates extra features
CScape CScape predicts the oncogenic status (disease-driver or neutral) of somatic point mutations