RepServer: Antigen Receptor Repertoire Analysis Pipelines via the WWW

RepServer：通过 WWW 的抗原受体库分析管道

• 批准号: 8636990
• 负责人: LINDSAY G. COWELL
• 金额: $ 64.15万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8636990
• 关键词: Address; Algorithms; Antibodies; Antigen Receptors; Archives; Area; Autoimmune Diseases; Autoimmune Responses; Basic Science; Bioinformatics; Cells; Clinical; Computer software; Data; Data Analyses; Development; Diagnosis; Diagnostic; Disease; Event; Fc Receptor; Foundations; Future; Genes; Goals; Hand; Hematologic Neoplasms; High Performance Computing; Immune; Immune response; Immune system; Immunity; Immunologic Deficiency Syndromes; Individual; Infection; Internet; J segment gene; Jaw; Knowledge; Left; Manuals; Metadata; Methods; Modification; Nature; Organism; Output; Pathogenesis; Patient Monitoring; Pattern; Play; Reporting; Reproducibility; Research; Research Infrastructure; Research Personnel; Role; Software Tools; Somatic Mutation; Time; Translational Research; Translations; Vaccination; Vaccine Design; Vertebrates; Work; clinical practice; computer program; data acquisition; data management; design; improved; leukemia/lymphoma; next generation sequencing; novel therapeutics; prognostic; repository; research and development; response; senescence; software development; task analysis; tool; web site

DESCRIPTION (provided by applicant): An organism's ability to mount an effective immune response after infection or vaccination depends on the type of antibodies and antigen receptors produced by its immune system cells. This set of molecules also plays an important role in the pathogenesis of many kinds of disease, such as autoimmune disease, lymphoma, and leukemia. Thus, analysis of an individual's repertoire of such molecules is applied in a wide variety of basic research, research and development, and clinical contexts. Despite the importance and complexity of repertoire analysis, there is currently no suite of software tools for analysis of repertoire data. Tools exist for only a subset of analysis tasks, and those that do exist were developed for use on a single project by a single research group. These tools do not function together and cannot be utilized in new studies without modification that requires bioinformatics expertise, leaving researchers to perform repetitive and error-prone tasks by hand, to develop internal, idiosyncratic algorithms not easily generalizable or systematically applied, and to expend significant manual labor reformatting primary and derived data for passing between tools. This approach is not only error-prone and time- and labor-intensive, but it comes at the expense of reproducibility, both within and between research groups. We propose to address this critical barrier to progress by developing RepServer, a suite of interoperable repertoire analysis tools and an interface that allows users to upload a set of repertoire sequences and pass them through a seamless workflow that executes all steps in the analysis and generates an analysis report complete with data summary tables, statistical analyses, figures, and workflow logs. The impact of RepServer will be significant. RepServer will improve the efficiency of repertoire analysis by reducing duplication of effort and eliminating the need for significant manual manipulation of data. The latter will in turn improve the accuracy and reliability of analyses by reducing errors. RepServer will make sophisticated computational analyses of repertoires accessible to bench biologists and clinicians. RepServer will provide the infrastructure for reproducibility, a critical step towards translation of repertoire analysis into clinical settings. RepServer will have impact in all areas of research, development, and clinical practice that rely on repertoire analysis.

描述（由申请人提供）：生物体在感染或接种疫苗后产生有效免疫应答的能力取决于其免疫系统细胞产生的抗体和抗原受体的类型。这组分子在许多疾病的发病机制中也起着重要作用，如自身免疫性疾病、淋巴瘤和白血病。因此，对个体的此类分子库的分析应用于各种各样的基础研究、研发和临床背景中。尽管库分析的重要性和复杂性，目前还没有一套软件工具用于分析库数据。现有的工具仅用于分析任务的一个子集，并且那些确实存在的工具是由单个研究小组开发用于单个项目的。这些工具不能一起工作，不能在新的研究中使用，而不需要修改，需要生物信息学专业知识，让研究人员手工执行重复和容易出错的任务，开发内部的，特殊的算法不容易推广或系统应用，并花费大量的手工劳动重新格式化的主要和衍生数据之间的工具。这种方法不仅容易出错，而且耗时耗力，而且以牺牲研究组内部和研究组之间的可重复性为代价。我们建议通过开发RepServer来解决这一阻碍进展的关键障碍，这是一套可互操作的库分析工具和一个界面，允许用户上传一组库序列并将其传递给无缝工作流程，该工作流程执行分析中的所有步骤并生成包含数据汇总表、统计分析、图表和工作流程日志的分析报告。RepServer的影响将是巨大的。RepServer将通过减少重复工作和消除对大量人工操作数据的需要，提高剧目分析的效率。后者又将通过减少误差来提高分析的准确性和可靠性。RepServer将为实验室生物学家和临床医生提供复杂的计算分析。RepServer将提供再现性的基础设施，这是将库分析转化为临床环境的关键一步。RepServer将对依赖于剧目分析的研究、开发和临床实践的所有领域产生影响。