Identification and analysis of deleterious human SNPs.

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TitleIdentification and analysis of deleterious human SNPs.
Publication TypeJournal Article
Year of Publication2006
AuthorsYue, P, Moult, J
JournalJ Mol Biol
Volume356
Issue5
Pagination1263-74
Date Published2006 Mar 10
ISSN0022-2836
KeywordsAnimals, Databases, Protein, DNA Mutational Analysis, Evolution, Molecular, Genetic Predisposition to Disease, Genome, Humans, Mice, Mice, Knockout, Polymorphism, Single Nucleotide, Proteins, Sensitivity and Specificity
Abstract

We have developed two methods of identifying which non-synonomous single base changes have a deleterious effect on protein function in vivo. One method, described elsewhere, analyzes the effect of the resulting amino acid change on protein stability, utilizing structural information. The other method, introduced here, makes use of the conservation and type of residues observed at a base change position within a protein family. A machine learning technique, the support vector machine, is trained on single amino acid changes that cause monogenic disease, with a control set of amino acid changes fixed between species. Both methods are used to identify deleterious single nucleotide polymorphisms (SNPs) in the human population. After carefully controlling for errors, we find that approximately one quarter of known non-synonymous SNPs are deleterious by these criteria, providing a set of possible contributors to human complex disease traits.

DOI10.1016/j.jmb.2005.12.025
Alternate JournalJ. Mol. Biol.
PubMed ID16412461
Grant ListLM07174 / LM / NLM NIH HHS / United States