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Bioinformatics. 2008 Oct 1;24(19):2209-14. doi: 10.1093/bioinformatics/btn386. Epub 2008 Jul 24.

GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population.

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  • 1Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX13TG, UK.

Abstract

Current genotyping algorithms typically call genotypes by clustering allele-specific intensity data on a single nucleotide polymorphism (SNP) by SNP basis. This approach assumes the availability of a large number of control samples that have been sampled on the same array and platform. We have developed a SNP genotyping algorithm for the Illumina Infinium SNP genotyping assay that is entirely within-sample and does not require the need for a population of control samples nor parameters derived from such a population. Our algorithm exhibits high concordance with current methods and >99% call accuracy on HapMap samples. The ability to call genotypes using only within-sample information makes the method computationally light and practical for studies involving small sample sizes and provides a valuable independent quality control metric for other population-based approaches.

AVAILABILITY:

http://www.stats.ox.ac.uk/~giannoul/GenoSNP/.

PMID:
18653518
[PubMed - indexed for MEDLINE]
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