SNPs

Single Nucleotide Polymorhisms

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Contents

   

Further reading and resources

Adzhubei et al. (2013) Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum Genet Chapter 7:Unit7.20. (pmid: 23315928)

[ PubMed ] [ DOI ] PolyPhen-2 (Polymorphism Phenotyping v2), available as software and via a Web server, predicts the possible impact of amino acid substitutions on the stability and function of human proteins using structural and comparative evolutionary considerations. It performs functional annotation of single-nucleotide polymorphisms (SNPs), maps coding SNPs to gene transcripts, extracts protein sequence annotations and structural attributes, and builds conservation profiles. It then estimates the probability of the missense mutation being damaging based on a combination of all these properties. PolyPhen-2 features include a high-quality multiple protein sequence alignment pipeline and a prediction method employing machine-learning classification. The software also integrates the UCSC Genome Browser's human genome annotations and MultiZ multiple alignments of vertebrate genomes with the human genome. PolyPhen-2 is capable of analyzing large volumes of data produced by next-generation sequencing projects, thanks to built-in support for high-performance computing environments like Grid Engine and Platform LSF.

Sim et al. (2012) SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res 40:W452-7. (pmid: 22689647)

[ PubMed ] [ DOI ] The Sorting Intolerant from Tolerant (SIFT) algorithm predicts the effect of coding variants on protein function. It was first introduced in 2001, with a corresponding website that provides users with predictions on their variants. Since its release, SIFT has become one of the standard tools for characterizing missense variation. We have updated SIFT's genome-wide prediction tool since our last publication in 2009, and added new features to the insertion/deletion (indel) tool. We also show accuracy metrics on independent data sets. The original developers have hosted the SIFT web server at FHCRC, JCVI and the web server is currently located at BII. The URL is http://sift-dna.org (24 May 2012, date last accessed).