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Nucleic Acids Research 2005 33(17):e142; doi:10.1093/nar/gni142
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Published online 30 September 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oxfordjournals.org

Methods Online

PPC: an algorithm for accurate estimation of SNP allele frequencies in small equimolar pools of DNA using data from high density microarrays

Jesper Brohede1,2, Rob Dunne1,3, James D. McKay4,5 and Garry N. Hannan1,2,*

1CSIRO Preventative Health National Research Flagship Sydney, Australia 2CSIRO Molecular and Health Technologies Sydney, Australia 3CSIRO Mathematical and Information Sciences Sydney, Australia 4Menzies Research Institute, University of Tasmania Hobart, Australia 5International Agency for Research on Cancer Lyon, France

*To whom correspondence should be addressed. Tel. +61 2 9490 5054; Fax +61 2 9490 5010; Email: Garry.Hannan{at}CSIRO.au

Received August 11, 2005. Revised September 1, 2005. Accepted September 1, 2005.

Robust estimation of allele frequencies in pools of DNA has the potential to reduce genotyping costs and/or increase the number of individuals contributing to a study where hundreds of thousands of genetic markers need to be genotyped in very large populations sample sets, such as genome wide association studies. In order to make accurate allele frequency estimations from pooled samples a correction for unequal allele representation must be applied. We have developed the polynomial based probe specific correction (PPC) which is a novel correction algorithm for accurate estimation of allele frequencies in data from high-density microarrays. This algorithm was validated through comparison of allele frequencies from a set of 10 individually genotyped DNA's and frequencies estimated from pools of these 10 DNAs using GeneChip 10K Mapping Xba 131 arrays. Our results demonstrate that when using the PPC to correct for allelic biases the accuracy of the allele frequency estimates increases dramatically.


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