A GENOMEWIDE ASSOCIATION STUDY OF LIVER CANCER

肝癌的全基因组关联研究

• 批准号: 7723374
• 负责人: ROBERT J CLIFFORD
• 金额: $ 0.05万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7723374
• 关键词: Bioinformatics; Biological Assay; Computer Retrieval of Information on Scientific Projects Database; Data; Data Set; Disease; Funding; Genome; Genotype; Grant; Haplotypes; Human; Institution; Malignant neoplasm of liver; Measures; Research; Research Personnel; Resources; Sampling; Single Nucleotide Polymorphism; Source; United States National Institutes of Health; computing resources; genetic variant; genome wide association study; member; population genetics laboratory

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. Members of the NCI Laboratory of Population Genetics Bioinformatics Core will use TeraGrid computing resources to perform a genome-wide association study of liver cancer. The study will involve 250 cases and 500 controls. Each sample will be genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 microarray, which contains probe sets assaying 900,000 single nucleotide polymorphisms. The resulting data set will have 675 million data points. TeraGrid computing resources will be used primarily to: 1) predict haplotypes 2), identify haplotype tag SNPs and 3) measure the correlation between genetic variants and disease state.

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。 NCI 人口遗传学生物信息学核心实验室的成员将使用 TeraGrid 计算资源进行肝癌的全基因组关联研究。该研究将涉及 250 个病例和 500 个对照。每个样本都将使用 Affymetrix 全基因组人类 SNP Array 6.0 微阵列进行基因分型，该微阵列包含可检测 900,000 个单核苷酸多态性的探针组。生成的数据集将有 6.75 亿个数据点。 TeraGrid 计算资源将主要用于：1) 预测单倍型 2) 识别单倍型标签 SNP 以及 3) 测量遗传变异与疾病状态之间的相关性。