Validation and extension of an empirical Bayes method for SNP calling on Affymetrix microarrays |
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| Authors: | Shin Lin Benilton Carvalho David J Cutler Dan E Arking Aravinda Chakravarti Rafael A Irizarry |
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| Affiliation: | (1) McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, N. Broadway, Baltimore, MD 21205, USA;(2) Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, North Wolfe St. E3035, Baltimore, MD 21205, USA |
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| Abstract: | ![]()
Multiple algorithms have been developed for the purpose of calling single nucleotide polymorphisms (SNPs) from Affymetrix microarrays. We extend and validate the algorithm CRLMM, which incorporates HapMap information within an empirical Bayes framework. We find CRLMM to be more accurate than the Affymetrix default programs (BRLMM and Birdseed). Also, we tie our call confidence metric to percent accuracy. We intend that our validation datasets and methods, refered to as SNPaffycomp, serve as standard benchmarks for future SNP calling algorithms. |
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