A k-mer-based search engine for sequencing databases

基于 k-mer 的测序数据库搜索引擎

• 批准号: 2138585
• 负责人: Paul Medvedev
• 金额: $ 80万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138585&HistoricalAwards=false
• 关键词: mer; based; search; engine; sequencing

Databases with biological sequencing data hold a treasure trove of biological data that can be used to aid experimental design and find relevant prior experiments for new biological projects. However, these rapidly growing archives are heavily under-utilized due to our inability to rapidly query the raw data within them. Just as search engines transformed our ability to broadly and deeply access information online, search indices have the potential to revolutionize the ways in which sequencing data in these archives is used. In this project methods to enable fast and easy access to these databases will be developed. This will contribute to the “Googlification” of life-science data, spurring broad scientific advances. Additionally, as part of the project, a “Writing in CS” course as well as an exercise booklet for probabilistic analysis of algorithms will be developed. Workshops on emerging methods for sequence analysis will be organized, and training to underrepresented undergraduates, graduate students and postdocs will be provided. This project advances research across all areas of life science that work with sequencing data. It createspowerful indexing data structures and querying algorithms for databases of sequencing experiments. This can allow biologists to query sequencing databases to find experiments which express a certain transcript of interest, show differential levels of expression between two transcripts, contain a known splice junction or gene fusion, or contain a small genome of interest. This project will facilitate a biologist to be able to execute many biologically-stated queries on a database of raw DNA and RNA sequencing experiments. The results of this project will be available on http://medvedevgroup.com/nsf-iibr-project.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.

具有生物测序数据的数据库保存着生物数据的宝库，这些数据可用于辅助实验设计并为新的生物项目找到相关的先前实验。然而，由于我们无法快速查询其中的原始数据，这些快速增长的档案严重未得到充分利用。正如搜索引擎改变了我们广泛深入地访问在线信息的能力一样，搜索索引有可能彻底改变这些档案中测序数据的使用方式。在这个项目中，将开发能够快速和方便地访问这些数据库的方法。这将有助于生命科学数据的“谷歌化”，推动广泛的科学进步。此外，作为该项目的一部分，将开发“CS写作”课程以及算法概率分析练习手册。将组织关于新出现的序列分析方法的讲习班，并将向代表性不足的本科生、研究生和博士后提供培训。该项目推进了与测序数据相关的生命科学所有领域的研究。它为测序实验数据库提供了强大的索引数据结构和查询算法。这可以允许生物学家查询测序数据库，以找到表达某种感兴趣的转录本、显示两种转录本之间的差异表达水平、包含已知的剪接点或基因融合或包含感兴趣的小基因组的实验。该项目将促进生物学家能够对原始DNA和RNA测序实验的数据库执行许多生物学陈述的查询。该项目的结果将在www.example.com上公布http://medvedevgroup.com/nsf-iibr-project.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

Efficient mapping of accurate long reads in minimizer space with mapquik.

• DOI: 10.1101/gr.277679.123
• 发表时间: 2023-07
• 期刊: GENOME RESEARCH
• 影响因子: 7
• 作者: Ekim, Baris;Sahlin, Kristoffer;Medvedev, Paul;Berger, Bonnie;Chikhi, Rayan
• 通讯作者: Chikhi, Rayan

Compression Algorithm for Colored de Bruijn Graphs

彩色 de Bruijn 图的压缩算法

• 发表时间: 2023
• 期刊: 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023
• 作者: Rahman, Amatur;Dufresne, Yoann;Medvedev, Paul
• 通讯作者: Medvedev, Paul

Exact Sketch-Based Read Mapping

精确的基于草图的读取映射

• 发表时间: 2023
• 期刊: 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023
• 作者: Schulz, Tizian;Medvedev, Paul
• 通讯作者: Medvedev, Paul