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.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 Affymetrix SNP阵列已被广泛用于单核苷酸多态性（SNP）基因型调用和DNA拷贝数变化推断。尽管许多方法在这些领域的准确性很高，但大多数研究很少关注探针与靶向等位基因序列的杂交建模，这可能会极大地影响准确性。在这项研究中，我们解决了这个问题，并证明了与不匹配核苷酸（HWMMN）的杂交发生在所有SNP探针集中，并且对等位基因浓度（ACS）的估计有关键作用。我们通过结合自由能和结合亲和力研究序列结合，并开发探针强度复合表示（PICR）模型。 PICR模型允许通过统计回归在给定SNP处估算ACS。此外，我们通过使用每个样本的估计AC与参考样品的估计AC的比率，可以在单个SNP基因座的拷贝数估计中实现合理的拷贝数估计准确性，并可以揭示出异常位点SNP的细微基因型结构，从而证明PICR模型可以在单个SNP基因座处实现合理的精度。我们还使用HAPMAP数据证明了PICR模型在样本，实验室甚至数组平台之间始终如一地产生准确的SNP基因型调用。