ABI Development: systemPipeR - automated NGS workflow and report generation environment
ABI Development: systemPipeR - automated NGS workflow and report generation environment
批准号:
1661152
负责人:
Thomas Girke
金额:
$64.89万
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
项目状态:
已结题
起止时间:
2017-05-15 至 2022-04-30
中文摘要
下一代测序(NGS)通过允许研究人员对基因组和转录组进行常规测序,彻底改变了生物学许多领域的研究方式。然而,对NGS数据的分析仍然是有效利用该技术的一个主要障碍。虽然已经投入了大量的努力来开发专用于NGS实验的各个分析步骤的软件,但是目前没有足够的资源来将各个软件组件集成到能够以时间有效和可再现的方式从头到尾运行大多数类型的NGS应用的分析的自动化工作流程中。这个开发项目将通过增强systemPipeR(一个流行的R/Bioconductor软件包)来满足这一需求。该项目将对广泛的科学界和我们的社会产生重大影响,通过允许将NGS数据转化为生物学相关知识,具有时效性和可复制性。这将加速学术界和工业界的许多研究和发现项目,NGS技术在其中发挥着重要作用。将为基因组和计算生物学交叉点的跨学科培训提供广泛的教育资源。将向科学家、博士后研究人员、研究生和本科生提供培训。代表性不足群体的成员将参与该项目的各个方面,同时支持多样性。将提供广泛的在线辅导,以最大限度地扩大这些活动的教育范围。该项目的具体目标是:(目的1)增强systemPipeR?的用户界面和工作流设计框架将大大简化运行工作流、生成自动报告和设计新工作流的过程。它还将提高用户友好性,使systemPipeR对R和非R用户以及没有任何生物信息学专业知识的生物学家同样有用。这一目标的执行计划包括设计一个中央工作流程控制用户界面和适应新的社区标准,以进一步提高分析工作流程的可重复性。(AIM 2)将为广泛的其他NGS应用开发自动化分析工作流程。这些工作流程中的大多数将与相应的NGS应用领域的专家合作设计。社区的建议也将纳入其中。将为受支持的NGS应用程序提供示例模板,以便使用一个完全填充了所有输入数据和环境设置的命令创建工作流实例。(AIM 3)该项目还将重点关注社区融合以及当前和未来用户提供的绩效评估。这包括用户贡献代码或整个工作流的选项,以及对目标受众进行广泛的培训,以使用systemPipeR和相关资源分析NGS数据。systemPipeR项目网站的URL是:http://girke.bioinformatics.ucr.edu/systemPipeR。
英文摘要
Next-generation sequencing (NGS) has revolutionized how research is carried out in many areas of biology by allowing researchers to sequence genomes and transcriptomes on a routine basis. However, the analysis of NGS data remains a major obstacle to the efficient utilization of the technology. While substantial effort has been invested on the development of software dedicated to the individual analysis steps of NGS experiments, insufficient resources are currently available for integrating the individual software components into automated workflows capable of running the analysis of most types of NGS applications from start-to-finish in a time-efficient and reproducible manner. This Development project will address this need by enhancing systemPipeR, a popular R/Bioconductor software package. The project will have significant impact on a wide range of scientific communities and our society at large by allowing to translate NGS data into biologically relevant knowledge in a time-efficient and reproducible manner. This will accelerate many research and discovery projects in academia and industry, where NGS technologies play an important role. Extensive educational resources for interdisciplinary training at the intersect of genome and computational biology will be provided. Training will be offered to scientists, postdoctoral researchers, graduate and undergraduate students. Members of underrepresented groups will participate in all aspects of this project while supporting diversity. Extensive online tutorials will be provided to maximize the educational outreach of the activities. The specific aims of this project are: (AIM 1) Enhancements to systemPipeR?s user interface and the workflow design framework will greatly simplify the process of running workflows, generating automated reports and designing new workflows. It will also improve user-friendliness to make systemPipeR equally useful for R and non-R users, as well as biologists without any expert knowledge in bioinformatics. The execution plan of this aim includes the design of a central workflow control user interface and the adaptation of new community standards to further increase the reproducibility of analysis workflows. (AIM 2) Automated analysis workflows will be developed for a wide range of additional NGS applications. Most of these workflows will be designed in collaboration with experts of the corresponding NGS application areas. Suggestions from the community will be incorporated as well. Sample templates will be provided for the supported NGS applications to create workflow instances with a single command fully populated with all input data and environment settings. (AIM 3) The project will also have a strong focus on community integration and performance evaluations provided by its current and future users. This includes options for users to contribute code or entire workflows, and extensive training of the target audience to analyze NGS data with systemPipeR and related resources. The URL of the systemPipeR project website is: http://girke.bioinformatics.ucr.edu/systemPipeR.
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DOI:
10.1126/sciadv.aaz7628
发表时间:
2020-10
期刊:
Science advances
影响因子:
13.6
作者:
[Lombard DB, Kohler WJ, Guo AH, Gendron C, Han M, Ding W, Lyu Y, Ching TT, Wang FY, Chakraborty TS, Nikolovska-Coleska Z, Duan Y, Girke T, Hsu AL, Pletcher SD, Miller RA]
通讯作者:
Miller RA
DOI:
10.1186/s12859-016-1241-0
发表时间:
2016-09-20
期刊:
BMC bioinformatics
影响因子:
3
作者:
[H Backman TW, Girke T]
通讯作者:
Girke T
DOI:
10.1073/pnas.1701474114
发表时间:
2017-02
期刊:
Proceedings of the National Academy of Sciences
影响因子:
--
作者:
[Xiufeng Zhang;E. Aksoy;T. Girke;A. Raikhel;Fedor V. Karginov]
通讯作者:
Xiufeng Zhang;E. Aksoy;T. Girke;A. Raikhel;Fedor V. Karginov
HOTAIRM1 lncRNA is downregulated in clear cell renal cell carcinoma and inhibits the hypoxia pathway
DOI:
10.1016/j.canlet.2019.12.022
发表时间:
2020-01-01
期刊:
CANCER LETTERS
影响因子:
9.7
作者:
[Hamilton, Michael J., Young, Matthew, Martinez, Ernest]
通讯作者:
Martinez, Ernest
Research Infrastructure: MRI: Acquisition of a Big Data HPC Cluster for Interdisciplinary Research and Training
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批准号:2215705
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项目类别:Standard Grant
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资助金额:$66.0万
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财政年份:2022
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负责人:Thomas Girke
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依托单位:
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负责人:Thomas Girke
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项目类别:--
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资助金额:40万元
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负责人:Vikrant Gupta
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依托单位: