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. 2005 Jul 1;33(Web Server issue):W480-2.
doi: 10.1093/nar/gki372.

nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms

Lei Bao  1 , Mi Zhou, Yan Cui
Affiliations

nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms

Lei Bao et al. Nucleic Acids Res. .

Abstract

Nonsynonymous single nucleotide polymorphisms (nsSNPs) are prevalent in genomes and are closely associated with inherited diseases. To facilitate identifying disease-associated nsSNPs from a large number of neutral nsSNPs, it is important to develop computational tools to predict the nsSNP's phenotypic effect (disease-associated versus neutral). nsSNPAnalyzer, a web-based software developed for this purpose, extracts structural and evolutionary information from a query nsSNP and uses a machine learning method called Random Forest to predict the nsSNP's phenotypic effect. nsSNPAnalyzer server is available at http://snpanalyzer.utmem.edu/.

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Figures

Figure 1
Figure 1
The program design and data flow of nsSNPAnalyzer.
Figure 2
Figure 2
The output of nsSNPAnalyzer. (A) The main output page of nsSNPAnalyzer. The user can click the icon to see the interpretation of each field. (B) An example of local sequence alignment spanning the nsSNP (D7N). The original amino acid (D) is highlighted in blue, and the mutated amino acid (N) is highlighted in red.
See this image and copyright information in PMC

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