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.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 Affymetrix SNP 芯片已广泛用于单核苷酸多态性 (SNP) 基因型识别和 DNA 拷贝数变异推断。尽管许多方法在这些领域已经实现了高精度，但大多数研究很少关注探针与脱靶等位基因序列杂交的建模，这会极大地影响准确性。在这项研究中，我们解决了这个问题，并证明了错配核苷酸 (HWMMN) 的杂交发生在所有 SNP 探针组中，并且对等位基因浓度 (AC) 的估计具有关键影响。我们通过结合自由能和结合亲和力研究序列结合，并开发了探针强度复合表示（PICR）模型。 PICR 模型允许通过统计回归估计给定 SNP 的 AC。此外，我们利用已知真实拷贝数的细胞系数据证明，通过使用每个样本的估计 AC 与参考样本的 AC 的比率，PICR 模型可以在单个 SNP 位点的拷贝数估计中实现合理的准确性，并可以揭示异常位点的 SNP 的微妙基因型结构。我们还利用 HapMap 数据证明，PICR 模型能够在样本、实验室甚至阵列平台上一致地产生准确的 SNP 基因型识别。