Tuning big data analysis infrastructure for HIV research

调整艾滋病毒研究的大数据分析基础设施

• 批准号: 9511742
• 负责人: ANTON NEKRUTENKO
• 金额: $ 69.13万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-26 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9511742
• 关键词: AIDS/HIV problem; Address; Adoption; Algorithms; Back; Base Sequence; Benchmarking; Big Data; Biological; Biomedical Research; Collection; Communities; Community Developments; Computer software; Custom; Data; Data Analyses; Data Analytics; Data Reporting; Development; Education and Outreach; Educational Curriculum; Educational workshop; Fostering; Foundations; Funding; Galaxy; Genome; Genomics; Genotype-Tissue Expression Project; Goals; HIV; Haplotypes; Human; Human Microbiome; Individual; Informatics; Learning Skill; Minor; Mutation; Phylogenetic Analysis; Privacy; Process; Reproducibility; Research; Research Infrastructure; Research Personnel; Resources; Running; Series; Site; Software Tools; Standardization; System; Technology; The Cancer Genome Atlas; Time; Training; Translating; Variant; Work; Writing; analytical method; computer infrastructure; computing resources; cost; data management; data visualization; design; experience; genomic tools; improved; next generation sequencing; novel; open source; pathogen; reconstruction; software development; success; tool; tool development; undergraduate student; virtual

Abstract: The state of big data analytics in the field of HIV/AIDS research is critically lacking. Decreasing cost of sequencing stimulated the development of novel software tools and analysis frameworks. The bulk of these efforts has been driven by truly expansive (and well-funded) collaborative projects such as the 1000 genomes, ENCODE, modENCODE, GTEx, the Human Microbiome, the Cancer Genome Atlas, and others. While these projects hardened many aspects of NGS data analysis and manipulation, as well as established standards for data representation (e.g. BAM, VCF, CRAM formats) they were facing a set of challenges that is markedly distinct from those faced by HIV researchers, e.g. long stable genomes with few mutations (i.e., human) versus short variable genomes with many mutations (i.e., HIV). Consequently, the development of HIV-specific tools and applications for next generation sequencing (NGS) has largely been the domain of individual labs, independently designing sensible ad hoc, yet disaggregated, solutions to common problems, resulting in a fragmented field largely without accepted standards and gaps between available solutions and the needs of end users. The current practice of writing “full-stack” custom in-house solutions for NGS analyses is not scalable, not maintainable, largely fails to leverage the developments from other domains of NGS data analysis, and hampers the adoption of this transformative technology in HIV research. The specific aims of this proposal address practical aspects of HIV/AIDS-related NGS analysis by assembling proven and newly developed tools and modules into “data to answer” series of workflows, and creating a publicly available and accessible turnkey solution suitable for a large proportion of HIV/AIDS researchers needing to perform routine and bespoke analyses of NGS data..

摘要： 艾滋病毒/艾滋病研究领域的大数据分析严重缺乏。测序成本的降低刺激了新型软件工具和分析框架的开发。这些努力的大部分是由真正广泛的（和资金充足的）合作项目推动的，如1000个基因组，ENCODE，modENCODE，GTEx，人类微生物组，癌症基因组图谱等。虽然这些项目强化了NGS数据分析和操作的许多方面，以及数据表示的既定标准（例如BAM，VCF，CRAM格式），但它们面临着一系列与HIV研究人员所面临的挑战明显不同的挑战，例如具有很少突变的长期稳定基因组（即，人）与具有许多突变的短可变基因组（即，HIV）。因此，针对下一代测序（NGS）的HIV特异性工具和应用的开发在很大程度上是各个实验室的领域，独立设计针对常见问题的合理的临时但分散的解决方案，导致该领域基本上没有公认的标准，并且在可用的解决方案和最终用户的需求之间存在差距。目前为NGS分析编写“全栈”自定义内部解决方案的做法不可扩展，不可维护，在很大程度上未能利用NGS数据分析其他领域的发展，并阻碍了这种变革性技术在艾滋病毒研究中的采用。该提案的具体目标是解决与艾滋病毒/艾滋病相关的NGS分析的实际问题，将经过验证的和新开发的工具和模块组装成“数据回答”系列工作流程，并创建一个公开提供和可访问的交钥匙解决方案，适用于需要对NGS数据进行常规和定制分析的大部分艾滋病毒/艾滋病研究人员。