Introduction

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

Publications

  1. GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population.
    Cite this
    Giannoulatou E, Yau C, Colella S, Ragoussis J, Holmes CC, 2008-10-01 - Bioinformatics (Oxford, England)

Credits

  1. Eleni Giannoulatou
    Developer

    Department of Statistics, University of Oxford, United Kingdom of Great Britain and Northern Ireland

  2. Christopher Yau
    Developer

  3. Stefano Colella
    Developer

  4. Jiannis Ragoussis
    Developer

  5. Christopher C Holmes
    Investigator

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Summary
AccessionBT007028
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC
User InterfaceTerminal Command Line
Download Count0
Submitted ByChristopher C Holmes