Advanced Gene Mapping Course

高级基因作图课程

• 批准号: 10347368
• 负责人: SUZANNE M LEAL
• 金额: $ 8.01万
• 依托单位: ROCKEFELLER UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10347368
• 关键词: Admixture; Basic Science; Biological; Categories; Chromatin; Chromosome Mapping; Clinical; Cloud Computing; Communities; Complex; Complex Genetic Trait; Computer software; Computers; Data; Data Analyses; Data Files; Detection; Development; Disabled Persons; Disadvantaged; Disease; Ensure; Etiology; Exercise; Faculty; Family; Fees; Genes; Genetic; Genetic Epistasis; Genetic Predisposition to Disease; Genotype; Heritability; Human Gene Mapping; Individual; Knowledge; Libraries; Mediating; Mediation; Mendelian randomization; Meta-Analysis; Methodology; Methods; Methylation; Minority; Modality; Modeling; New York; New York City; Participant; Pathogenicity; Population; Postdoctoral Fellow; Quality Control; Research Personnel; Running; Sample Size; Sequence Analysis; Slide; Students; Susceptibility Gene; Testing; Training; Travel; Universities; Update; Variant; Woman; base; cost; data quality; data tools; disease diagnosis; doctoral student; epigenomics; experience; genetic analysis; genetic epidemiology; genome wide association study; human disease; improved; instructor; laptop; learning materials; lectures; pleiotropism; polygenic risk score; power analysis; pre-doctoral; programs; rare variant; skills; statistics; theories; tool; trait; transcriptome sequencing; web site

Project Summary The aim of this proposal is to hold an annual, full-week course in advanced gene mapping at The Rockefeller University in New York. The course is directed towards advanced researchers who are familiar with the fundamental aspects of statistical genetics but who need to become more proficient in the analysis of complex traits. Thirty-four students will be accepted to each course, and stipends, to cover travel costs, will be provided to ten participants who are either pre-doctoral students or post-doctoral fellows. The course consists of two components: lectures on important current topics in gene mapping, as well as hands-on exercises to be performed with the latest freeware software programs using cloud computing. The current emphasis of the course is analyses of sequence and other omics data. The next Advanced Gene Mapping course will be held January 27-31, 2020. The PI and five additional instructors who are experts in their respective fields will teach on a variety of topics that include: data quality control; qualitative and quantitative trait (population and family-based data) association analysis of whole-genome data (genotype, sequence, and imputed); controlling for population admixture and substructure; meta-analysis; sample size estimation and power calculations; detecting gene x gene interactions; analysis of epigenomic and RNAseq data; elucidating pleiotropy; functional prediction and variant annotation; estimation of polygenic risk scores; Mendelian randomization and mediation analysis; and fine mapping. A variety of freely available software including ANNOVAR, GCTA-MLMA, PAINTOR, LDpred, PrediXCan, R, SEQSpark, and VAT will be implemented to perform practical exercises. Since gene mapping is a quickly changing field, the topics and analytic programs will be updated annually to reflect the latest developments in the field of statistical genetics. Given the vast amounts of generated genetic data, it is essential to train researchers and give them the necessary information and tools for data analysis to elucidate the etiology of complex traits.

项目摘要 这项建议的目的是每年举办一次为期一周的高级基因图谱课程， 纽约的洛克菲勒大学。该课程是针对高级研究人员谁熟悉 统计遗传学的基本方面，但谁需要成为更精通的分析 复杂的特征。每门课程将招收34名学生，并提供助学金，以支付旅费， 将提供给十名参与者，他们是博士前学生或博士后研究员。过程 由两部分组成：关于基因图谱的重要当前主题的讲座，以及动手操作 使用云计算的最新免费软件程序进行练习。当前 本课程的重点是分析序列和其他组学数据。下一篇：Advanced Gene Mapping 课程将于2020年1月27日至31日举行。PI和另外五名教师谁是专家， 各个领域将教授各种主题，包括：数据质量控制;定性和定量 性状（基于群体和家族的数据）全基因组数据（基因型，序列， 和插补）;控制群体混合和亚结构;荟萃分析;样本量估计 和功效计算;检测基因X基因相互作用;表观基因组和RNAseq数据的分析; 阐明多效性;功能预测和变异注释;估计多基因风险评分; 孟德尔随机化和中介分析;精细绘图。各种免费软件 包括ANNOVAR、GCTA-MLMA、PAINTOR、LDpred、PrediXCan、R、SEQSpark和VAT， 进行实际演练。由于基因定位是一个快速变化的领域， 分析程序将每年更新，以反映统计领域的最新发展。 遗传学鉴于生成的基因数据量巨大，培训研究人员并提供 它们为数据分析提供了必要的信息和工具，以阐明复杂性状的病因。