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MetaDB 一种在非靶向 MS 代谢组学实验中的数据处理工作流程。

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

机构信息

Research and Innovation Centre, Fondazione E. Mach , San Michele all'Adige, Trento , Italy.

Research and Innovation Centre, Fondazione E. Mach , San Michele all'Adige, Trento , Italy ; Institute of Plant Sciences, Faculty of Agriculture, The Hebrew University of Jerusalem , Rehovot , Israel.

出版信息

Front Bioeng Biotechnol. 2014 Dec 16;2:72. doi: 10.3389/fbioe.2014.00072. eCollection 2014.

DOI:10.3389/fbioe.2014.00072
PMID:25566535
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4267269/
Abstract

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

摘要

由于其灵敏度和速度,基于质谱的分析技术被广泛应用于代谢组学中,以描述生物现象。为了解决元数据组织、质量评估、数据处理、数据存储,以及最终提交到公共存储库等问题,通常采用非交互式的生物信息学管道来补充用于数据初始检查和可视化的交互式软件。这些管道通常作为开源软件创建,允许对每个步骤进行完整和详尽的记录,从而确保广泛且通常昂贵的实验的分析具有可重复性。在本文中,我们将回顾构成这种数据处理管道的主要步骤,并在我们研究所最近开发的用于非靶向 MS 基代谢组学实验的开源软件的背景下对其进行讨论。该软件是通过将我们的 metaMS R 包与基于 Grails 的用户友好的网络应用程序集成而开发的。metaMS 负责数据预处理和注释,而接口则用于创建样本列表、组织数据存储以及生成质量评估的概览图。实验和生物学元数据以 ISA-Tab 格式存储,使得所提出的管道与 Metabolights 框架完全集成。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/1abae24d895c/fbioe-02-00072-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/0e964db89001/fbioe-02-00072-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/2751524b1baf/fbioe-02-00072-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/efa31b9c3108/fbioe-02-00072-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/1abae24d895c/fbioe-02-00072-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/0e964db89001/fbioe-02-00072-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/2751524b1baf/fbioe-02-00072-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/efa31b9c3108/fbioe-02-00072-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a9b/4267269/1abae24d895c/fbioe-02-00072-g004.jpg

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