SHF:Small: Reproducibility and Comprehensive Assessment of Next Generation Sequencing Bioinformatics Software

SHF:Small：下一代测序生物信息学软件的重现性和综合评估

基本信息

批准号：
1718479
负责人：
Srinivas Aluru
金额：
$ 50万
依托单位：
Georgia Tech Research Corporation
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-15 至 2023-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1718479&HistoricalAwards=false
关键词：
SHF Small Reproducibility Comprehensive Assessment

项目摘要

Next-generation sequencing refers to a collection of high throughput DNA sequencing technologies that have originated about a decade ago, and are now the de facto equipment underpinning all modern genomics studies due to their cost-effectiveness and ubiquity and versatility of use. This project is conducting comprehensive reproducibility and assessment experiments to characterize the state of the art in the field, and make the findings publicly visible and accessible. The project results are expected to become a valuable resource for practitioners, researchers, and the significantly large community of users of next generation sequencing bioinformatics. The project is involving several undergraduate students, and raising awareness of research integrity and reproducibility issues among young researchers.The project is establishing benchmark datasets to evaluate bioinformatics software for multiple next generation sequencers, multiple types of biological organisms, in multiple application contexts, and at multiple problem scales. The research spans assessment of software products for read error correction, read mapping to target genomes and reference databases, and assembly of genomes and transcriptomes. Reproducibility experiments are conducted to independently verify results of important software products based on results and datasets published in the literature. The software products are also evaluated on a range of metrics - quality of results, robustness and sensitivity to parameter values, run-time performance, memory usage, and ability to process real-world datasets. The project work will result in comprehensive recommendations available to practitioners as well as establishing state of the art to appropriately channel future research efforts.

下一代测序是指起源于大约十年前的一系列高通量 DNA 测序技术，由于其成本效益、普遍性和多功能性，现在已成为所有现代基因组学研究的事实上的设备。该项目正在进行全面的可重复性和评估实验，以表征该领域的最新技术，并使研究结果公开可见和易于获取。该项目结果预计将成为下一代测序生物信息学从业者、研究人员和广大用户社区的宝贵资源。该项目涉及多名本科生，旨在提高年轻研究人员对研究完整性和可重复性问题的认识。该项目正在建立基准数据集，以评估多个下一代测序仪、多种类型的生物有机体、在多种应用环境中的生物信息学软件。多个问题尺度。该研究涵盖用于读取错误校正的软件产品评估、目标基因组和参考数据库的读取映射以及基因组和转录组的组装。进行再现性实验，以根据文献中发表的结果和数据集独立验证重要软件产品的结果。软件产品还根据一系列指标进行评估——结果质量、鲁棒性和对参数值的敏感性、运行时性能、内存使用情况以及处理真实数据集的能力。该项目工作将为从业者提供全面的建议，并建立最先进的技术以适当地引导未来的研究工作。