Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.
Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.
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DOI：
10.1016/j.bbapap.2013.02.032
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发表时间：
2014-01
期刊：
影响因子：
--
通讯作者：
Vizcaíno JA
中科院分区：
文献类型：
--
作者：
Perez-Riverol Y;Wang R;Hermjakob H;Müller M;Vesada V;Vizcaíno JA
数据处理、管理和可视化是最先进的基于高通量质谱仪(MS)的蛋白质组学实验的核心和关键组件，并且通常是最耗时的步骤，特别是对于没有太多生物信息学支持的实验室。人们对蛋白质组学领域的兴趣与日俱增，引发了新软件库开发的增加，包括免费提供的软件和开放源码软件。从数据库搜索分析到识别结果的后处理，尽管这些库和包的目标可能有很大差异，但它们通常具有许多共同特征。常见用例包括处理蛋白质和多肽序列、解析来自各种蛋白质组学搜索引擎输出文件的结果以及MS相关信息(包括质谱图和色谱图)的可视化。在这篇综述中，我们提供了现有软件库和开源框架的概述，并提供了一些使用它们的免费可用应用程序的信息。这篇文章是题为：后鉴定时代的计算蛋白质组学特刊的一部分。客座编辑：马丁·艾森纳赫和克里斯蒂安·斯蒂芬。对现有的计算蛋白质组学开源软件的回顾。描述了一个典型的MS实验中每一步可用的软件。详细介绍了OpenMS、TPP、COMPONY、ProteoWizard、JPL、PROSE工具包。考虑了不同的编程语言(Java、Perl、C++或Python)。
Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. A review of existing open-source software for computational proteomics. Available software for each step in a typical MS experiment is described. OpenMS, TPP, compomics, ProteoWizard, JPL, PRIDE toolsuite are covered in detail. Different programming languages are considered (Java, Perl, C++ or Python).
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