A multi-array multi-SNP genotyping algorithm for affymetrix SNP microarrays
A multi-array multi-SNP genotyping algorithm for affymetrix SNP microarrays
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DOI：
10.1093/bioinformatics/btm131
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发表时间：
2007-06-15
期刊：
影响因子：
5.8
通讯作者：
Yeh, Ru-Fang
中科院分区：
文献类型：
--
作者：
Xiao, Yuanyuan;Segal, Mark R.;Yeh, Ru-Fang
动机：现代的疾病基因定位策略需要对基因组中大量已知的多态性位点进行有效的基因分型。基于杂交的DNA微阵列技术的灵敏性和高通量性质通过在单个测定中询问高达数十万个单核苷酸多态性（SNP）为这样的应用提供了理想的平台。与表达阵列的开发类似，这些基因分型阵列提出了许多数据分析挑战，这些挑战通常是平台特异性的。亲和SNP阵列，例如对每个已知SNP使用多组短寡核苷酸探针，并且需要有效的统计方法来联合收割机组合这些探针强度，以产生可靠和准确的基因型调用。我们开发了一种用于Affyssin SNP阵列的集成多SNP、多阵列基因型调用算法MAMS，其结合了单阵列多SNP（SAMS）和多阵列，单SNP（MASS）调用以提高基因型调用的准确性，而不需要像其他多阵列方法那样训练数据或计算密集型归一化程序。该算法使用rescovery技术和基于模型的聚类来获得基于单个阵列的基因型调用，随后通过基于（MASS）聚类的竞争性基因型调用来细化。重新排序方案限制了单阵列分析的计算，因此易于扩展，这在扩大每个阵列的SNP数量方面很重要。MASS更新旨在改善对非典型SNP的要求，这些SNP具有等位基因不平衡的结合亲和力，在没有其他阵列信息的情况下难以进行基因分型。使用一个公开的数据集的HapMap样本从Affysses，和独立的调用替代基因分型方法从HapMap项目，我们表明，我们的方法执行竞争力现有的方法。
Motivation: Modern strategies for mapping disease loci require efficient genotyping of a large number of known polymorphic sites in the genome. The sensitive and high-throughput nature of hybridization-based DNA microarray technology provides an ideal platform for such an application by interrogating up to hundreds of thousands of single nucleotide polymorphisms (SNPs) in a single assay. Similar to the development of expression arrays, these genotyping arrays pose many data analytic challenges that are often platform specific. Affymetrix SNP arrays, e.g. use multiple sets of short oligonucleotide probes for each known SNP, and require effective statistical methods to combine these probe intensities in order to generate reliable and accurate genotype calls.Results: We developed an integrated multi-SNP, multi-array genotype calling algorithm for Affymetrix SNP arrays, MAMS, that combines single-array multi-SNP (SAMS) and multi-array, single-SNP (MASS) calls to improve the accuracy of genotype calls, without the need for training data or computation-intensive normalization procedures as in other multi-array methods. The algorithm uses resampling techniques and model-based clustering to derive single array based genotype calls, which are subsequently refined by competitive genotype calls based on (MASS) clustering. The resampling scheme caps computation for single-array analysis and hence is readily scalable, important in view of expanding numbers of SNPs per array. The MASS update is designed to improve calls for atypical SNPs, harboring allele-imbalanced binding affinities, that are difficult to genotype without information from other arrays. Using a publicly available data set of HapMap samples from Affymetrix, and independent calls by alternative genotyping methods from the HapMap project, we show that our approach performs competitively to existing methods.