Perez-Riverol Yasset, Wang Rui, Hermjakob Henning, Müller Markus, Vesada Vladimir, Vizcaíno Juan Antonio
EMBL Outstation, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK; Department of Proteomics, Center for Genetic Engineering and Biotechnology, Ciudad de la Habana, Cuba.
Biochim Biophys Acta. 2014 Jan;1844(1 Pt A):63-76. doi: 10.1016/j.bbapap.2013.02.032. Epub 2013 Mar 1.
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.
数据处理、管理和可视化是基于高通量质谱(MS)的蛋白质组学实验中核心且关键的组成部分,并且往往是一些最耗时的步骤,对于那些没有太多生物信息学支持的实验室来说尤其如此。蛋白质组学领域日益增长的兴趣引发了新软件库开发的增加,包括免费可用的开源软件。从数据库搜索分析到鉴定结果的后处理,尽管这些库和软件包的目标可能有很大差异,但它们通常具有一些共同特征。常见的用例包括蛋白质和肽序列的处理、各种蛋白质组学搜索引擎输出文件结果的解析以及质谱相关信息(包括质谱图和色谱图)的可视化。在本综述中,我们概述了现有的软件库、开源框架,并且还提供了一些使用它们的免费可用应用程序的信息。本文是名为“鉴定后时代的计算蛋白质组学”特刊的一部分。客座编辑:Martin Eisenacher和Christian Stephan。