I-Corps: Software for the Next Generation Sequence Analysis for Homogeneous Populations

I-Corps：用于同质群体的下一代序列分析的软件

• 批准号: 1910957
• 负责人: Aleksandr Zelikovskiy
• 金额: $ 5万
• 依托单位: Georgia State University Research Foundation, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910957&HistoricalAwards=false
• 关键词: Corps; Software; Next; Generation; Sequence

The broader impact/commercial potential of this I-Corps project is improving public health systems by predicting, monitoring, and preventing outbreaks of infectious diseases. The broader applications of the proposed software system for analysis of sequencing data will also include tracing cancer development and analyzing its potential to grow, mutate, and resist treatment. The proposed software system will be integrated into laboratories' pipelines for clustering and assembling sequencing reads into complete genomic sequences. The proposed statistical algorithms will analyze the sequencing data more accurately which improves sequencing quality without an increase in sequencing depth thus further reducing sequencing cost. The proposed software system will attract epidemiological and medical laboratories by more accurate analysis and cost reduction of high-throughput sequencing.This I-Corps project deals with growing demand for powerful computational tools for analyzing high-throughput sequencing data. Existing software tools can successfully extract different sequences form the same sample but, in many applications, (such as an investigation of outbreaks of infectious disease, cancer research, and genome-wide association studies) it is necessary to distinguish multiple distinct yet closely related genomic sequences. The main obstacle for such studies is a high sequencing error rate and short length of reads produced by high-throughput sequencing technologies. The proposed software system can overcome these obstacles by using statistical algorithms capable of sorting out the sequencing errors delivering complete genomic sequences and accurately identifying point mutations distinguishing closely related sequences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该I-Corps项目的更广泛的影响/商业潜力是通过预测，监测和防止传染病爆发来改善公共卫生系统。提出的软件系统用于分析测序数据的更广泛应用还将包括追踪癌症的发展并分析其生长，突变和抵抗治疗的潜力。提出的软件系统将集成到实验室的管道中，以聚类和组装测序读取将读取为完整的基因组序列。提出的统计算法将更准确地分析测序数据，从而提高测序质量而不增加测序深度，从而进一步降低了测序成本。 提出的软件系统将通过更准确的分析和降低高通量测序的成本来吸引流行病学和医疗实验室。本I-Corps项目涉及对分析高通量测序数据的强大计算工具的增长需求。现有的软件工具可以成功提取不同的序列形成相同的样本，但是在许多应用中（例如对传染病，癌症研究和全基因组关联研究的爆发的研究），有必要区分多个不同的不同但密切相关的基因组序列。此类研究的主要障碍是高通量测序技术产生的高测误率和短长的读取。提出的软件系统可以通过使用能够对测序错误进行排列的统计算法来克服这些障碍，从而提供完整的基因组序列，并准确地识别与密切相关序列的点突变。该奖项反映了NSF的法定任务，并通过基金会的知识优点和广泛的影响来评估NSF的法定任务，并被认为是值得的支持。