Literature DB >> 14751981

Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms.

Robert J Clifford1, Michael N Edmonson, Cu Nguyen, Kenneth H Buetow.   

Abstract

MOTIVATION: Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans. SNPs causing amino acid substitutions are of particular interest as candidates for loci affecting susceptibility to complex diseases, such as diabetes and hypertension. To efficiently screen SNPs for disease association, it is important to distinguish neutral variants from deleterious ones.
RESULTS: We describe the use of Pfam protein motif models and the HMMER program to predict whether amino acid changes in conserved domains are likely to affect protein function. We find that the magnitude of the change in the HMMER E-value caused by an amino acid substitution is a good predictor of whether it is deleterious. We provide internet-accessible display tools for a genomewide collection of SNPs, including 7391 distinct non-synonymous coding region SNPs in 2683 genes. AVAILABILITY: http://lpgws.nci.nih.gov/cgi-bin/GeneViewer.cgi

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Year:  2004        PMID: 14751981     DOI: 10.1093/bioinformatics/bth029

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  43 in total

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2.  The road from next-generation sequencing to personalized medicine.

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3.  Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel.

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4.  Modeling mutant/wild-type interactions to ascertain pathogenicity of PROKR2 missense variants in patients with isolated GnRH deficiency.

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5.  Computational approaches to identify functional genetic variants in cancer genomes.

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Review 6.  Computational algorithms for in silico profiling of activating mutations in cancer.

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Review 8.  Towards precision medicine: advances in computational approaches for the analysis of human variants.

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Review 9.  Analytical methods for inferring functional effects of single base pair substitutions in human cancers.

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10.  Inferring selection on amino acid preference in protein domains.

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Journal:  Mol Biol Evol       Date:  2008-12-18       Impact factor: 16.240

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