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

高通量测序（HTS）技术的最新进展为研究基因组结构、功能和进化提供了前所未有的机会，并正在深刻地改变基因组研究。然而，充分发挥高温超导技术的潜力需要复杂的数据分析方法。本研究项目旨在开发有效的计算方法，用于从HTS数据中重建全谱单倍型序列。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，研究人员将开发三种新的HTS应用方法，即(a)重建二倍体基因组序列，包括每个CNV拷贝的完整单倍型序列，(b)重建可选剪接异构体序列及其频率，以及(c)重建病毒准种序列及其频率。该项目的主要成果将包括开发针对这些问题的综合分析工具包，以及将向研究社区免费提供的高质量开源软件实现。该项目将为康涅狄格大学和佐治亚州立大学的本科生和研究生提供参与生物信息学研究的机会，并将特别鼓励妇女和代表性不足的群体参与。

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.