III-CXT-Small: Algorithmic strategies for genotype-phenotype correlations

III-CXT-Small:基因型-表型相关性的算法策略

基本信息

  • 批准号:
    0810905
  • 负责人:
  • 金额:
    $ 45万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2008
  • 资助国家:
    美国
  • 起止时间:
    2008-09-01 至 2012-08-31
  • 项目状态:
    已结题

项目摘要

In the wake of new sequencing and genotyping technologies, whole genome studies are now being undertaken to understand the genetic basis of phenotypes. Many of the principles underlying the measurement of genotype-phenotype relationships, as well as computing related population genetic parameters, are relatively well understood. However, the upcoming technologies dramatically change the scale and scope of these studies, which already encompass tens of thousands of individuals over a genome-wide region. The analysis of this data requires novel algorithmic and statistical techniques. This project focuseson a subset of the problems that could arise in a typical whole-genome based association study. These include:(a) Phasing of genotypes into haplotypes using overlapping sequence data, and the application of this algorithm to phasing individual human sequences; the availability of high coverage long sequence data will make this approach the method of choice for phasing in the near future. (b) Fast filtering for pairs of loci that interactively influence a phenotype and its application to multiple-locus testing of common disease phenotypes. The proposed work reduces the computational bottleneck in multiple locus testing.(c) Detection of regions under balancing selection. Available tests are focused on detection of regions under positive selection. The proposed research looks for evidence of balancing selection in the genome, with specific attention on genes associated with bipolar disorder.(d) Reconstruction of regulatory pathways using associations between genetic variation and gene-expression.All software from this research is freely available as source-code, or as web-tools for academic, research and non-commercial purposes in accordance with University policy. Further information on the project may be found at the project web site: http://bix.ucsd.edu/algen
在新的测序和基因分型技术之后,现在正在进行全基因组研究以了解表型的遗传基础。基因型-表型关系的测量以及相关群体遗传参数的计算的许多基本原理相对较好地理解。然而,即将到来的技术极大地改变了这些研究的规模和范围,这些研究已经涵盖了全基因组区域的数万人。这些数据的分析需要新的算法和统计技术。这个项目集中在一个典型的全基因组关联研究中可能出现的问题的一个子集上。(a)使用重叠序列数据将基因型分阶段确定为单体型,并将这种算法应用于对单个人类序列进行分阶段确定;高覆盖率长序列数据的可用性将使这种方法成为不久的将来进行分阶段确定的首选方法。(b)交互影响表型的基因座对的快速过滤及其在常见疾病表型多基因座检测中的应用。所提出的工作减少了多位点测试的计算瓶颈。(c)平衡选择下的区域检测。可用的测试集中在检测正选择下的区域。这项拟议中的研究寻找基因组中平衡选择的证据,特别关注与双相情感障碍相关的基因。(d)使用遗传变异和基因表达之间的关联重建调控途径。根据大学政策,本研究的所有软件都可以作为源代码或作为学术,研究和非商业目的的网络工具免费获得。有关该项目的更多信息,请访问项目网站:http://bix.ucsd.edu/algen

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Vineet Bafna其他文献

Coordinated inheritance of extrachromosomal DNAs in cancer cells
癌细胞中外染色体 DNA 的协同遗传
  • DOI:
    10.1038/s41586-024-07861-8
  • 发表时间:
    2024-11-06
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    King L. Hung;Matthew G. Jones;Ivy Tsz-Lo Wong;Ellis J. Curtis;Joshua T. Lange;Britney Jiayu He;Jens Luebeck;Rachel Schmargon;Elisa Scanu;Lotte Brückner;Xiaowei Yan;Rui Li;Aditi Gnanasekar;Rocío Chamorro González;Julia A. Belk;Zhonglin Liu;Bruno Melillo;Vineet Bafna;Jan R. Dörr;Benjamin Werner;Weini Huang;Benjamin F. Cravatt;Anton G. Henssen;Paul S. Mischel;Howard Y. Chang
  • 通讯作者:
    Howard Y. Chang
Engineered extrachromosomal oncogene amplifications promote tumorigenesis
工程化染色体外癌基因扩增促进肿瘤发生
  • DOI:
    10.1038/s41586-024-08318-8
  • 发表时间:
    2024-12-18
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Davide Pradella;Minsi Zhang;Rui Gao;Melissa A. Yao;Katarzyna M. Gluchowska;Ylenia Cendon-Florez;Tanmay Mishra;Gaspare La Rocca;Moritz Weigl;Ziqi Jiao;Hieu H. M. Nguyen;Marta Lisi;Mateusz M. Ozimek;Chiara Mastroleo;Kevin Chen;Felix Grimm;Jens Luebeck;Shu Zhang;Andrea Alice Zolli;Eric G. Sun;Bhargavi Dameracharla;Zhengqiao Zhao;Yuri Pritykin;Carlie Sigel;Howard Y. Chang;Paul S. Mischel;Vineet Bafna;Cristina R. Antonescu;Andrea Ventura
  • 通讯作者:
    Andrea Ventura
Deciphering the genetic basis of common diseases by integrated functional annotation of common and rare variants
  • DOI:
    10.1186/gb-2010-11-s1-i8
  • 发表时间:
    2010-10-11
  • 期刊:
  • 影响因子:
    9.400
  • 作者:
    Olivier Harismendy;Gaurav Bhatia;Nazli G Rahim;Vikas Bansal;Masakazu Nakano;Michael Scott;Xiaoyun Wang;Colette Dib;Edouard Turlotte;Nathaniel Heintzman;Sarah S Murray;Jean-Francois Deleuze;Jack C Sipe;Bing Ren;Vineet Bafna;Eric J Topol;Kelly A Frazer
  • 通讯作者:
    Kelly A Frazer
A method for tracking cell migration in vivo based on deep learning with target detection
一种基于深度学习目标检测的体内细胞迁移跟踪方法
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Tsubasa Mizugaki;Utkrisht Rajkumar;Kenji Fujimoto;Hironori Shigeta;Shigeto Seno;Yutaka Uchida;Masaru Ishii;Vineet Bafna;Hideo Matsuda
  • 通讯作者:
    Hideo Matsuda
Three-dimensional genome landscape of primary human cancers
原发性人类癌症的三维基因组图谱
  • DOI:
    10.1038/s41588-025-02188-0
  • 发表时间:
    2025-05-12
  • 期刊:
  • 影响因子:
    29.000
  • 作者:
    Kathryn E. Yost;Yanding Zhao;King L. Hung;Kaiyuan Zhu;Duo Xu;M. Ryan Corces;Shadi Shams;Bryan H. Louie;Shahab Sarmashghi;Laksshman Sundaram;Jens Luebeck;Stanley Clarke;Ashley S. Doane;Jeffrey M. Granja;Hani Choudhry;Marcin Imieliński;Andrew D. Cherniack;Ekta Khurana;Vineet Bafna;Ina Felau;Jean C. Zenklusen;Peter W. Laird;Christina Curtis;William J. Greenleaf;Howard Y. Chang
  • 通讯作者:
    Howard Y. Chang

Vineet Bafna的其他文献

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{{ truncateString('Vineet Bafna', 18)}}的其他基金

Collaborative Research: ABI Innovation: Computational population-genetic analysis for detection of soft selective sweeps
合作研究:ABI 创新:用于检测软选择性扫描的计算群体遗传分析
  • 批准号:
    1458557
  • 财政年份:
    2015
  • 资助金额:
    $ 45万
  • 项目类别:
    Standard Grant
III: Small: Algorithms for decoding complex patterns of genomic variation
III:小:解码基因组变异复杂模式的算法
  • 批准号:
    1318386
  • 财政年份:
    2013
  • 资助金额:
    $ 45万
  • 项目类别:
    Continuing Grant
AF: Small: Algorithms for Genetics: Epistatic Interactions, Haplotype Assembly, and Selection Signatures
AF:小:遗传学算法:上位相互作用、单倍型组装和选择签名
  • 批准号:
    1115206
  • 财政年份:
    2011
  • 资助金额:
    $ 45万
  • 项目类别:
    Standard Grant
Novel Algorithms for NcRNA Discovery and RNA Structure Prediction
NcRNA 发现和 RNA 结构预测的新算法
  • 批准号:
    0516440
  • 财政年份:
    2005
  • 资助金额:
    $ 45万
  • 项目类别:
    Standard Grant

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