Unknown

Dataset Information

IMHOTEP-a composite score integrating popular tools for predicting the functional consequences of non-synonymous sequence variants.


ABSTRACT: The in silico prediction of the functional consequences of mutations is an important goal of human pathogenetics. However, bioinformatic tools that classify mutations according to their functionality employ different algorithms so that predictions may vary markedly between tools. We therefore integrated nine popular prediction tools (PolyPhen-2, SNPs&GO, MutPred, SIFT, MutationTaster2, Mutation Assessor and FATHMM as well as conservation-based Grantham Score and PhyloP) into a single predictor. The optimal combination of these tools was selected by means of a wide range of statistical modeling techniques, drawing upon 10 029 disease-causing single nucleotide variants (SNVs) from Human Gene Mutation Database and 10 002 putatively ‘benign’ non-synonymous SNVs from UCSC. Predictive performanc

SUBMITTER: Knecht C 

PROVIDER: S-EPMC5388428 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature