Evaluating the accuracy of a functional SNP annotation system.
Many common and chronic diseases are influenced at some level by genetic variation. Research done in population genetics, specifically in the area of single nucleotide polymorphisms (SNPs) is critical to understanding human genetic variation. A key element in assessing role of a given SNP is determining if the variation is likely to result in change in function. The SNP Integration Tool (SNPit) is a comprehensive tool that integrates diverse, existing predictors of SNP functionality, providing the user with information for improved association study analysis. To evaluate the SNPit system, we developed an alternative gold standard to measure accuracy using sensitivity and specificity. The results of our evaluation demonstrated that our alternative gold standard produced encouraging results.
Shen
Terry H
TH
Departments of Biomedical & Health Informatics, University of Washington, Seattle, WA, USA. hyshen@u.washington.edu
Carlson
Christopher S
CS
Tarczy-Hornoch
Peter
P
D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D014644:Genetic Variation; D020641:Polymorphism, Single Nucleotide; D012984:Software