As an important feature for studying the
deleteriousness of an nsSNP, the conservation score is used by most of prediction methods with their own way of calculation.
The online free tool Combined Annotation-Dependent Depletion (CADD, http://cadd.gs.washington.edu/),[sup][19] a newly developed framework that integrates diverse annotations into a single quantitative score (C-score) to measure the
deleteriousness of SNVs and small InDels, was used to evaluate the pathogenicity of the deletion.
Computational tools for protein-sequence-based prediction of
deleteriousness fall into two categories: constraint-based predictors such as MAPP and SIFT, and trained classifiers such as MutationTaster and polyPhen.
According to the SIFT analysis, 75 of 345 nsSNPs were classified as being deleterious (for some SNPs, there was low confidence in the findings regarding
deleteriousness).
Lopez-Bigas, "Improving the assessment of the outcome of nonsynonymous SNVs with a consensus
deleteriousness score, Condel," The American Journal of Human Genetics, vol.
MetaSVM is a support vector machine based prediction, which classifies amino acid substitutions as tolerated or damaging by incorporating
deleteriousness scores produced by 9 individual algorithms: SIFT, PolyPhen-2, GERP++, Mutation Taster, Mutation Assessor, FATHMM, LRT, SiPhy, and PhyloP.