GENOTYPE AND COPY NUMBER CALLING

基因型和拷贝数检测

• 批准号: 8171736
• 负责人: Robert C. Elston
• 金额: $ 0.49万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8171736
• 关键词: Address; Affect; Affinity; Alleles; Attention; Binding; Cell Line; Computer Retrieval of Information on Scientific Projects Database; Copy Number Polymorphism; DNA copy number; Data; Free Energy; Funding; Genotype; Grant; Institution; Laboratories; Methods; Modeling; Nucleotides; Regression Analysis; Research; Research Personnel; Resources; Sampling; Single Nucleotide Polymorphism; Source; Structure; United States National Institutes of Health

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms.

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 Affymetrix SNP阵列已被广泛应用于单核苷酸多态(SNP)基因分型和DNA拷贝数变异推断。虽然许多方法在这些领域取得了很高的准确性，但大多数研究都很少关注探针与靶外等位基因序列的杂交建模，这对准确性有很大影响。在这项研究中，我们解决了这个问题，并证明了与错配核苷酸的杂交(HWMMN)发生在所有SNP探针组中，并对等位基因浓度(ACS)的估计具有关键影响。我们通过结合自由能和结合亲和力来研究序列结合，并建立了探针强度复合表示(PICR)模型。PICR模型允许通过统计回归来估计给定SNP时的ACS。此外，我们用已知真实拷贝数的细胞系数据证明，PICR模型可以通过估计每个样本的AC与参考样本的AC之比来估计单个SNP基因座的拷贝数，并可以揭示异常基因座上SNPs的微妙基因结构。我们还用HapMap数据演示了PICR模型跨样本、实验室甚至跨阵列平台一致地产生准确的SNP基因型调用。