BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI
BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI
复制标题
BASTet：通过 OpenMSI 对质谱成像数据进行可共享和可重复的分析和可视化
DOI：
10.1109/tvcg.2017.2744479
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发表时间：
2018
影响因子：
5.2
通讯作者：
B. Bowen
中科院分区：
文献类型：
--
作者：
O. Rübel;B. Bowen
质谱成像（MSI）是一种变革性的成像方法，支持对复杂样品的化学成分和空间异质性进行非靶向定量测量，在生命科学、生物能源和健康领域具有广泛的应用。虽然MSI数据可以常规收集，但其广泛应用目前受到缺乏易于访问的分析方法的限制，这些方法可以处理MSI实验产生的大小，体积，多样性和复杂性的数据。尖端分析方法的开发和应用是MSI研究新科学发现、医学诊断和商业创新的核心驱动力。然而，缺乏共享、应用和复制分析的手段阻碍了新MSI分析方法的广泛应用、验证和使用。为了解决这一核心挑战，我们介绍了伯克利分析和存储工具包（BASTet），一个新的框架，可共享和可重复的数据分析，支持标准化的数据和分析接口，集成的数据存储，数据出处，工作流管理，和一个广泛的集成工具。基于BASTe，我们描述了OpenMSI质谱成像科学网关的扩展，以实现基于Web的数据分析和衍生数据产品的共享、重用、分析和可视化。我们展示了BASTet和OpenMSI在实践中的应用，以识别和比较小鼠大脑中的特征子结构，其化学成分通过MSI测量。
Mass spectrometry imaging (MSI) is a transformative imaging method that supports the untargeted, quantitative measurement of the chemical composition and spatial heterogeneity of complex samples with broad applications in life sciences, bioenergy, and health. While MSI data can be routinely collected, its broad application is currently limited by the lack of easily accessible analysis methods that can process data of the size, volume, diversity, and complexity generated by MSI experiments. The development and application of cutting-edge analytical methods is a core driver in MSI research for new scientific discoveries, medical diagnostics, and commercial-innovation. However, the lack of means to share, apply, and reproduce analyses hinders the broad application, validation, and use of novel MSI analysis methods. To address this central challenge, we introduce the Berkeley Analysis and Storage Toolkit (BASTet), a novel framework for shareable and reproducible data analysis that supports standardized data and analysis interfaces, integrated data storage, data provenance, workflow management, and a broad set of integrated tools. Based on BASTet, we describe the extension of the OpenMSI mass spectrometry imaging science gateway to enable web-based sharing, reuse, analysis, and visualization of data analyses and derived data products. We demonstrate the application of BASTet and OpenMSI in practice to identify and compare characteristic substructures in the mouse brain based on their chemical composition measured via MSI.
影响因子：
62.1
作者：
Chughtai, Kamila;Heeren, Ron M. A.
通讯作者：
Heeren, Ron M. A.