Advanced Gene Mapping Course

高级基因作图课程

基本信息

  • 批准号:
    10347368
  • 负责人:
  • 金额:
    $ 8.01万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

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.
项目总结

项目成果

期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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{{ truncateString('SUZANNE M LEAL', 18)}}的其他基金

Elucidating the Genetic Etiology of Intellectual Disability in African, Asian, and European Families
阐明非洲、亚洲和欧洲家庭智力障碍的遗传病因
  • 批准号:
    10660541
  • 财政年份:
    2023
  • 资助金额:
    $ 8.01万
  • 项目类别:
Gene discovery in multi-ethnic late-onset Alzheimer's disease families
多种族晚发性阿尔茨海默病家族的基因发现
  • 批准号:
    10640970
  • 财政年份:
    2020
  • 资助金额:
    $ 8.01万
  • 项目类别:
Gene discovery in multi-ethnic late-onset Alzheimer's disease families
多种族迟发性阿尔茨海默病家族的基因发现
  • 批准号:
    10186680
  • 财政年份:
    2020
  • 资助金额:
    $ 8.01万
  • 项目类别:
Gene discovery in multi-ethnic late-onset Alzheimer's disease families
多种族迟发性阿尔茨海默病家族的基因发现
  • 批准号:
    10434636
  • 财政年份:
    2020
  • 资助金额:
    $ 8.01万
  • 项目类别:
Identification and Functional Evaluation of Autosomal Recessive Nonsyndromic Hearing Impairment Genes in sub-Saharan Africans
撒哈拉以南非洲人常染色体隐性非综合征性听力障碍基因的鉴定和功能评估
  • 批准号:
    10468748
  • 财政年份:
    2018
  • 资助金额:
    $ 8.01万
  • 项目类别:
Identification and Functional Evaluation of Autosomal Recessive Nonsyndromic Hearing Impairment Genes in sub-Saharan Africans
撒哈拉以南非洲人常染色体隐性非综合征性听力障碍基因的鉴定和功能评估
  • 批准号:
    10238026
  • 财政年份:
    2018
  • 资助金额:
    $ 8.01万
  • 项目类别:
Computational tools for sequence-based large-scale epidemiology studies
基于序列的大规模流行病学研究的计算工具
  • 批准号:
    9901082
  • 财政年份:
    2016
  • 资助金额:
    $ 8.01万
  • 项目类别:
Computational tools for sequence-based large-scale epidemiology studies
基于序列的大规模流行病学研究的计算工具
  • 批准号:
    9078292
  • 财政年份:
    2016
  • 资助金额:
    $ 8.01万
  • 项目类别:
Advanced Gene Mapping Course
高级基因作图课程
  • 批准号:
    9208387
  • 财政年份:
    2014
  • 资助金额:
    $ 8.01万
  • 项目类别:
Advanced Gene Mapping Course
高级基因作图课程
  • 批准号:
    8824548
  • 财政年份:
    2014
  • 资助金额:
    $ 8.01万
  • 项目类别:

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