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PPC:一种使用高密度微阵列数据准确估计小等摩尔DNA池中SNP等位基因频率的算法。

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

作者信息

Brohede Jesper, Dunne Rob, McKay James D, Hannan Garry N

机构信息

CSIRO Preventative Health National Research Flagship, Sydney, Australia.

出版信息

Nucleic Acids Res. 2005 Sep 30;33(17):e142. doi: 10.1093/nar/gni142.

Abstract

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.

摘要

对DNA池中等位基因频率进行稳健估计,有可能降低基因分型成本,和/或增加参与研究的个体数量。在非常大的人群样本集中,需要对数十万遗传标记进行基因分型,例如全基因组关联研究。为了从混合样本中准确估计等位基因频率,必须对等位基因代表性不均一进行校正。我们开发了基于多项式的探针特异性校正(PPC)方法,这是一种用于从高密度微阵列数据中准确估计等位基因频率的新型校正算法。通过比较一组10个单独基因分型的DNA的等位基因频率,以及使用GeneChip 10K Mapping Xba 131阵列从这10个DNA的混合样本中估计的频率,对该算法进行了验证。我们的结果表明,当使用PPC校正等位基因偏差时,等位基因频率估计的准确性会显著提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6559/1240117/53c451040b28/gni142f1.jpg

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