III: Small: Collaborative Research: Reconstruction of Haplotype Spectra from High-Throughput Sequencing Data

III：小：合作研究：从高通量测序数据重建单倍型谱

• 批准号: 0916401
• 负责人: Aleksandr Zelikovskiy
• 金额: $ 22.44万
• 依托单位: Georgia State University Research Foundation, Inc.
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916401&HistoricalAwards=false
• 关键词: III; Small; Collaborative; Research; Reconstruction

Recent advances in high-throughput sequencing (HTS) technologies provide opportunities to study genome structure, function, and evolution at an unprecedented scale, and are profoundly transforming genomic research. However, fully realizing the potential of HTS technologies requires sophisticated data analysis methods. This research project is aimed at developing efficient computational methods for reconstructing the full spectrum of haplotype sequences from HTS data. Working in collaboration with molecular biologists from the University of Connecticut Health Center and the Centers for Disease Control, the investigators will develop methods enabling three novel applications of HTS, namely (a) reconstruction of diploid genome sequences, including complete haplotype sequences of each CNV copy, (b) reconstruction of alternative splicing isoform sequences and their frequencies, and (c) reconstruction of viral quasispecies sequences and their frequencies. Major outcomes of the project will include the development of a comprehensive analytical toolkit for these problems, and high-quality open source software implementations that will be made available free of charge to the research community. The project will provide opportunities for participation of undergraduate and graduate students in bioinformatics research at UCONN and Georgia State University, and will especially encourage participation of women and underrepresented groups.

高通量测序（HTS）技术的最新进展为研究基因组结构，功能和进化的机会提供了前所未有的规模，并且正在深刻改变基因组研究。但是，充分意识到HTS技术的潜力需要复杂的数据分析方法。该研究项目旨在开发有效的计算方法，用于重建来自HTS数据的全倍型序列。与康涅狄格大学健康中心和疾病控制中心的分子生物学家合作，研究人员将开发方法，使HTS的三个新颖应用，即（a）重建二倍体基因组序列的重建，包括每个CNV序列的完整单倍型序列，（b）替代性序列（b）及其季度的频繁（b）他们的频繁（b）他们的频繁（b）他们的频繁（b）他们的常数（b）他们的频繁（c）（b）他们的频繁（b）他们的频繁（c）（b）准序列序列及其频率。该项目的主要结果将包括针对这些问题的全面分析工具包的开发，以及将为研究社区免费提供的高质量开源软件实现。该项目将为UCONN和GEORGIA州立大学的生物信息学研究的本科生和研究生提供机会，并特别鼓励妇女和代表性不足的群体参与。