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Bioinformatics Advance Access published online on September 10, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm443
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A genotype calling algorithm for the Illumina BeadArray platform

Yik Y. Teo a,b,c,*, Michael Inouye b,c, Kerrin S. Small a,b, Rhian Gwilliam b, Panagiotis Deloukas b, Dominic P. Kwiatkowski a,b and Taane G. Clark a,b

aWellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, bWellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, cjoint authors.

*To whom correspondence should be addressed. Dr. Yik Y. Teo, E-mail: teo{at}well.ox.ac.uk


  Abstract

Motivation: Large-scale genotyping relies on the use of unsupervised automated calling algorithms to assign genotypes to hybridization data. A number of such calling algorithms have been recently established for the Affymetrix GeneChip genotyping technology. Here we present a fast and accurate genotype calling algorithm for the Illumina BeadArray genotyping platforms. As the technology moves towards assaying millions of genetic polymorphisms simultaneously, there is a need for an integrated and easy-to-use software for calling genotypes.

Results: We have introduced a model-based genotype calling algorithm which does not rely on having prior training data or require computationally intensive procedures. The algorithm can assign genotypes to hybridization data from thousands of individuals simultaneously and pools information across multiple individuals to improve the calling. The method can accommodate variations in hybridization intensities which result in dramatic shifts of the position of the genotype clouds by identifying the optimal coordinates to initialise the algorithm. By incorporating the process of perturbation analysis, we can obtain a quality metric measuring the stability of the assigned genotype calls. We show that this quality metric can be used to identify SNPs with low call rates and accuracy.

Availability: The C++ executable for the algorithm described here is available by request from the authors.

Contact: teo{at}well.ox.ac.uk and tgc{at}well.ox.ac.uk

Associate Editor: Prof. Martin Bishop

Received on January 31, 2007; revised on August 20, 2007; accepted on August 20, 2007

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