Here, we have introduced and discussed the FATHMM software and server: a species-independent method with optional species-specific weightings for the prediction of the functional effects of protein missense variants. Inspired by previous sequence-based computational prediction algorithms [Ng and Henikoff, 2001; Thomas et al., 2003], our unweighted/species-independent method interrogates sequence conservation through the underlying amino acid probabilities modeled by the internal match states of several HMMs representing the alignment of homologous sequences and conserved protein domains. Following a similar weighting scheme implemented in SNPs&GO [Calabrese et al., 2009], our weighted/species-specific method amalgamates sequence conservation within the HMMs with “pathogenicity weights” representing the relative frequencies of disease-associated and functionally neutral AASs mapping onto conserved protein domains. The pathogenicity weights incorporated here are not directly used to train for, or recognize, pathogenic sequences, and/or mutations. Instead, these weights are capable of recognizing protein domains (species-independent/evolutionary units) sensitive to or intolerant of missense mutations. Therefore, the pathogenicity weights implemented in FATHMM are also likely to represent an improvement for nonhuman organisms (especially those not too distantly related to human) [Ferrer-Costa et al., 2005].
