Improving genotype call accuracy

提高基因型识别准确性

• 批准号: 8707516
• 负责人: BRIAN LEE BROWNING
• 金额: $ 34.07万
• 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 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8707516
• 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; 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（由申请人提供）：新的测序技术和越来越密集的SNP阵列正在产生大量的遗传数据。样本量正在增加，基因型变异的范围正在扩大，包括结构和多等位基因变异。这项研究将开发改进的基因型调用方法，这些方法是为这些数据设计的，并以新颖而有力的方式使用来自大样本和相关个体的信息。结果将提高基因型数据的准确性，这将有利于所有关于健康和疾病的遗传决定因素的研究。

项目成果

Family studies of type 1 diabetes reveal additive and epistatic effects between MGAT1 and three other polymorphisms.

1 型糖尿病的家族研究揭示了 MGAT1 和其他三种多态性之间的加性和上位效应。

• DOI: 10.1038/gene.2014.7
• 发表时间: 2014
• 期刊: Genes and immunity
• 影响因子: 5
• 作者: Yu,Z;Li,CF;Mkhikian,H;Zhou,RW;Newton,BL;Demetriou,M
• 通讯作者: Demetriou,M

Pseudosibship methods in the case-parents design.

• DOI: 10.1002/sim.4397
• 发表时间: 2011-11-30
• 期刊: STATISTICS IN MEDICINE
• 影响因子: 2
• 作者: Yu, Zhaoxia;Deng, Li
• 通讯作者: Deng, Li

Family-based association tests using genotype data with uncertainty.

• DOI: 10.1093/biostatistics/kxr045
• 发表时间: 2012-04
• 期刊: Biostatistics
• 影响因子: 2.1
• 作者: Zhaoxia Yu