Improving genotype call accuracy

提高基因型识别准确性

• 批准号: 8539066
• 负责人: BRIAN LEE BROWNING
• 金额: $ 31.32万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-07 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8539066
• 关键词: African American; Algorithms; Benchmarking; Cardiovascular Diseases; Computer software; Data; Data Security; Data Set; Detection; Diabetes Mellitus; Diagnosis; Disease; European; Floods; Generations; Genetic; Genetic Determinism; Genetic Variation; Genotype; Gold; Haplotypes; Health; Hispanics; Individual; Methods; Modeling; Nucleotides; Outcome; Parents; Phase; Population; Prevention; Publishing; Research; Research Personnel; Risk; Sample Size; Sampling; Secure; Technology; United States; Variant; X Chromosome; data sharing; design; disorder risk; genetic pedigree; genetic variant; genome sequencing; improved; next generation; novel; offspring; open source; success

DESCRIPTION (provided by applicant): New sequencing technologies and increasingly dense SNP arrays are generating a flood of genetic data. Sample sizes are increasing and the spectrum of genotyped variation is broadening to include structural and multi-allelic variants. This research will develop improved genotype calling methods that are designed for these data and that use information from large sample sizes and from related individuals in novel and powerful ways. The result will be improved genotype data accuracy which will benefit all research on the genetic determinants of health and disease.

描述(申请人提供)：新的测序技术和日益密集的SNP阵列正在产生大量的基因数据。样本量在增加，基因分型变异的范围也在扩大，包括结构和多等位基因变异。这项研究将开发针对这些数据设计的改进的基因型呼唤方法，并以新颖而有力的方式使用来自大样本和相关个人的信息。其结果将是提高基因数据的准确性，这将有利于对健康和疾病的遗传决定因素的所有研究。