Computational Tools for Analysis and Visualization of Quality Control Issues in Metabolomic Data
用于代谢组数据质量控制问题分析和可视化的计算工具
基本信息
- 批准号:10005202
- 负责人:
- 金额:$ 43.36万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-09-01 至 2022-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdoptionAffectAlgorithmic SoftwareAlgorithmsAttentionBeechBioinformaticsBiologicalBiologyBiomedical ResearchBiometryCancer CenterClinicalClinical MedicineCollaborationsCommunitiesComputer softwareCore FacilityCountryCustomDNADataDetectionDevelopmentDiagnosisDiseaseDocumentationEducational workshopEnvironmental Risk FactorFacultyFeedbackFundingGalaxyGenomicsGoalsInternationalLaboratoriesLeadershipLettersMapsMass Spectrum AnalysisMissionModelingMolecular ProfilingPlug-inProcessProteinsProteomicsQuality ControlRNAReproducibilityResearchResearch PersonnelResourcesSamplingSoftware EngineeringSourceSystemTestingThe Cancer Genome AtlasTrainingTranslatingVariantVisualVisualizationWorkbasebioinformatics toolbuilt environmentcloud basedcomputerized toolscomputing resourcesdata qualityexperienceexperimental studyflexibilityimprovedinnovationinstrumentinteroperabilitymembermetabolomicsmetabolomics resourcemultidisciplinarymultiple data sourcesnext generationopen sourceprogramssoftware developmenttooltranscriptomicstranslational scientisttrenduser-friendlyweb portalweb sitewebinarworking group
项目摘要
* * * Abstract * * *
In omic studies of all types (e.g., genomic, transcriptomic, proteomic, metabolomic), technical batch effects
pose a fundamental challenge to quality control and reproducibility. The possibilities for serious error are
greatly magnified in metabolomics, however, due to a range of possible platform, operator, instrument, and
environmental factors that can cause batch (or trend) effects. Hence, there is a need for routine surveillance
and correction of batch effects within and across metabolomics laboratories and technological platforms.
Accordingly, we propose here to develop the MetaBatch algorithms, computational tool, and web portal.
For development of MetaBatch, we will leverage our experience in developing MBatch, a tool that became
indispensible for quality-control of data in all 33 projects of The Cancer Genome Atlas (TCGA) program. Our
first aim is to translate the successful quality control model from TCGA to metabolomics by customizing and
extending the MBatch pipeline for detection, quantitation, diagnosis, interpretation, and correction of batch and
trend effects. The second aim is to develop and incorporate innovative metabolomics-specific algorithms,
including major visualization resources such as our interactive Next-Generation Clustered Heat Maps. The
third aim is to distribute MetaBatch to the research community as open-source software and in cloud-based
and Galaxy versions. The fourth aim is to provide plug-in capability for integration of MetaBatch with other
metabolomic resources, prominently including Metabolomics Workbench (in collaboration with Dr. Shankar
Subramaniam) and others developed within the Common Fund Metabolomics Program. Our fifth aim is to
promote MetaBatch actively and interact extensively with other Consortium members and the metabolomics
research community. With active support from MD Anderson Faculty and Academic Development, we will
provide documentation, tutorials, videos, demonstrations, and training to accelerate use and to solicit feedback
on limitations, possible improvements, and additional modules that would be useful in real-world workflows.
We bring a variety of assets to the project, including: the MBatch resource as a starting point for software
development; multidisciplinary expertise in bioinformatics, biostatistics, software engineering, biology, and
clinical medicine; PIs with a combined 21 years of experience in molecular profiling studies of clinical disease
(in a consortial context); international leadership in batch effects analysis; a software engineering team with a
track record of producing high-end, highly visual bioinformatics packages and websites; a team of 20 Analysts
whose expertise can be called on; extensive computing resources, including one of the most powerful
academically based machines in the world; strong institutional support; and close working relationships with
first-class basic, translational, and clinical researchers throughout MD Anderson, one of the foremost cancer
centers in the country. Our bottom-line mission will be to aid the research community's effort to improve rigor
and reproducibility in metabolomics for scientific understanding and to alleviate disease.
!
* * * 摘要 * *
在所有类型的组学研究中(例如,基因组学、转录组学、蛋白质组学、代谢组学)、技术批次效应
对质量控制和再现性提出了根本性的挑战。严重错误的可能性是
然而,由于一系列可能的平台、操作员、仪器和
可能导致批次(或趋势)效应的环境因素。因此,有必要进行例行监测
以及在代谢组学实验室和技术平台内部和之间校正批次效应。
因此,我们建议在这里开发MetaBatch算法,计算工具和门户网站。
对于MetaBatch的开发,我们将利用我们在开发MBatch方面的经验,MBatch是一个成为
对于癌症基因组图谱(TCGA)计划的所有33个项目的数据质量控制不可或缺。我们
第一个目标是通过定制和
扩展MBatch管道,用于批次的检测、定量、诊断、解释和校正,
趋势效应。第二个目标是开发和整合创新的代谢组学特定算法,
包括主要的可视化资源,如我们的交互式下一代加密热图。的
第三个目标是将MetaBatch作为开源软件和基于云的软件分发给研究社区。
Galaxy版本。第四个目标是提供插件功能,用于将MetaBatch与其他
代谢组学资源,主要包括代谢组学研究(与Shankar博士合作
Subramaniam)和其他在共同基金代谢组学计划内开发的。我们的第五个目标是
积极推广MetaBatch,并与其他联盟成员和代谢组学广泛互动
研究社区。在MD安德森学院和学术发展部的积极支持下,我们将
提供文档、教程、视频、演示和培训,以加快使用速度并征求反馈
关于限制、可能的改进以及在现实工作流中有用的其他模块。
我们为项目带来了各种资产,包括:作为软件起点的MBatch资源
开发;生物信息学,生物统计学,软件工程,生物学和
临床医学;具有21年临床疾病分子谱研究经验的PI
(in一个财团的背景下);在批量效应分析的国际领导地位;一个软件工程团队,
生产高端,高度可视化的生物信息学软件包和网站的跟踪记录;一个由20名分析师组成的团队
其专业知识可以调用;广泛的计算资源,包括最强大的
世界上以学术为基础的机器;强大的机构支持;以及与
一流的基础,翻译,和临床研究人员在整个MD安德森,最重要的癌症之一,
中心在该国。我们的底线使命将是帮助研究界努力提高严谨性
以及代谢组学的可重复性,以帮助科学理解和减轻疾病。
!
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Rehan Akbani其他文献
Rehan Akbani的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Rehan Akbani', 18)}}的其他基金
The Cancer Proteome Atlas: an Integrated Bioinformatics Resource for Functional Cancer Proteomic Data
癌症蛋白质组图谱:功能性癌症蛋白质组数据的综合生物信息学资源
- 批准号:
10653202 - 财政年份:2022
- 资助金额:
$ 43.36万 - 项目类别:
A Genome Data Analysis Center Focused on Batch Effect Analysis and Data Integration
专注于批量效应分析和数据集成的基因组数据分析中心
- 批准号:
10300778 - 财政年份:2021
- 资助金额:
$ 43.36万 - 项目类别:
A Genome Data Analysis Center Focused on Batch Effect Analysis and Data Integration
专注于批量效应分析和数据整合的基因组数据分析中心
- 批准号:
10689115 - 财政年份:2021
- 资助金额:
$ 43.36万 - 项目类别:
Computational Tools for Analysis and Visualization of Quality Control Issues in Metabolomic Data
用于代谢组数据质量控制问题分析和可视化的计算工具
- 批准号:
9615762 - 财政年份:2018
- 资助金额:
$ 43.36万 - 项目类别:
Computational Tools for Analysis and Visualization of Quality Control Issues in Metabolomic Data
用于代谢组数据质量控制问题分析和可视化的计算工具
- 批准号:
10251093 - 财政年份:2018
- 资助金额:
$ 43.36万 - 项目类别:
Batch effects in molecular profiling data on cancers: detection, quantitation, interpretation, and correction
癌症分子分析数据的批次效应:检测、定量、解释和校正
- 批准号:
9352299 - 财政年份:2016
- 资助金额:
$ 43.36万 - 项目类别:
Integrated analysis of protein expression data from the Reverse Phase Protein Array (RPPA) platform
对反相蛋白阵列 (RPPA) 平台的蛋白表达数据进行集成分析
- 批准号:
10005168 - 财政年份:2016
- 资助金额:
$ 43.36万 - 项目类别:
Batch effects in molecular profiling data on cancers: detection, quantitation, interpretation, and correction
癌症分子分析数据的批次效应:检测、定量、解释和校正
- 批准号:
9789027 - 财政年份:2016
- 资助金额:
$ 43.36万 - 项目类别:
Integrated analysis of protein expression data from the Reverse Phase Protein Array (RPPA) platform
对反相蛋白阵列 (RPPA) 平台的蛋白表达数据进行集成分析
- 批准号:
9789028 - 财政年份:2016
- 资助金额:
$ 43.36万 - 项目类别:
Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)
综合分析管道
- 批准号:
8546703 - 财政年份:2009
- 资助金额:
$ 43.36万 - 项目类别:
相似海外基金
WELL-CALF: optimising accuracy for commercial adoption
WELL-CALF:优化商业采用的准确性
- 批准号:
10093543 - 财政年份:2024
- 资助金额:
$ 43.36万 - 项目类别:
Collaborative R&D
Investigating the Adoption, Actual Usage, and Outcomes of Enterprise Collaboration Systems in Remote Work Settings.
调查远程工作环境中企业协作系统的采用、实际使用和结果。
- 批准号:
24K16436 - 财政年份:2024
- 资助金额:
$ 43.36万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Unraveling the Dynamics of International Accounting: Exploring the Impact of IFRS Adoption on Firms' Financial Reporting and Business Strategies
揭示国际会计的动态:探索采用 IFRS 对公司财务报告和业务战略的影响
- 批准号:
24K16488 - 财政年份:2024
- 资助金额:
$ 43.36万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 43.36万 - 项目类别:
EU-Funded
Assessing the Coordination of Electric Vehicle Adoption on Urban Energy Transition: A Geospatial Machine Learning Framework
评估电动汽车采用对城市能源转型的协调:地理空间机器学习框架
- 批准号:
24K20973 - 财政年份:2024
- 资助金额:
$ 43.36万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 43.36万 - 项目类别:
EU-Funded
Our focus for this project is accelerating the development and adoption of resource efficient solutions like fashion rental through technological advancement, addressing longer in use and reuse
我们该项目的重点是通过技术进步加快时装租赁等资源高效解决方案的开发和采用,解决更长的使用和重复使用问题
- 批准号:
10075502 - 财政年份:2023
- 资助金额:
$ 43.36万 - 项目类别:
Grant for R&D
Engage2innovate – Enhancing security solution design, adoption and impact through effective engagement and social innovation (E2i)
Engage2innovate — 通过有效参与和社会创新增强安全解决方案的设计、采用和影响 (E2i)
- 批准号:
10089082 - 财政年份:2023
- 资助金额:
$ 43.36万 - 项目类别:
EU-Funded
De-Adoption Beta-Blockers in patients with stable ischemic heart disease without REduced LV ejection fraction, ongoing Ischemia, or Arrhythmias: a randomized Trial with blinded Endpoints (ABbreviate)
在没有左心室射血分数降低、持续性缺血或心律失常的稳定型缺血性心脏病患者中停用β受体阻滞剂:一项盲法终点随机试验(ABbreviate)
- 批准号:
481560 - 财政年份:2023
- 资助金额:
$ 43.36万 - 项目类别:
Operating Grants
Collaborative Research: SCIPE: CyberInfrastructure Professionals InnoVating and brOadening the adoption of advanced Technologies (CI PIVOT)
合作研究:SCIPE:网络基础设施专业人员创新和扩大先进技术的采用 (CI PIVOT)
- 批准号:
2321091 - 财政年份:2023
- 资助金额:
$ 43.36万 - 项目类别:
Standard Grant