Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework.
Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework.
复制标题
使用Galaxy框架改善蛋白质组学分析的灵活且可访问的工作流程。
DOI：
10.1021/pr500812t
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发表时间：
2014-12-05
影响因子：
4.4
通讯作者：
Griffin, Timothy J.
中科院分区：
文献类型：
--
作者：
Jagtap, Pratik D.;Johnson, James E.;Onsongo, Getiria;Sadler, Fredrik W.;Murray, Kevin;Wang, Yuanbo;Shenykrnan, Gloria M.;Bandhakavi, Sricharan;Smith, Lloyd M.;Griffin, Timothy J.
关键词：
蛋白质基因组学将大规模基因组和转录组数据与基于质谱的蛋白质组数据相结合，以发现新的蛋白质序列变异并改进基因组注释。与传统的蛋白质组学应用相比，蛋白质组学分析需要许多额外的数据处理步骤。理想情况下，这些所需的步骤将通过单一软件平台进行集成和自动化，为湿台研究人员提供可访问性，并为用户特定的定制和新软件工具出现时的集成提供灵活性。为此，我们扩展了 Galaxy 生物信息学框架以促进蛋白质基因组分析。以人类唾液分析为例，我们通过创建模块化工作流程来展示 Galaxy 的灵活性，该工作流程结合了已建立和定制的软件工具，可提高蛋白质组结果的深度和质量。我们定制的基于 Galaxy 的软件包括自动批量模式 BLASTP 搜索和肽序列匹配评估器工具，两者都可用于评估假定的新型肽鉴定的准确性。我们复杂的工作流程（大约 140 个步骤）可以使用内置 Galaxy 功能轻松共享，以便其他人使用和定制。我们的结果为建立 Galaxy 框架作为新兴蛋白质组学领域的理想解决方案提供了蓝图。
Proteogenomics combines large-scale genomic and transcriptomic data with mass-spectrometry-based proteomic data to discover novel protein sequence variants and improve genome annotation. In contrast with conventional proteomic applications, proteogenomic analysis requires a number of additional data processing steps. Ideally, these required steps would be integrated and automated via a single software platform offering accessibility for wet-bench researchers as well as flexibility for user-specific customization and integration of new software tools as they emerge. Toward this end, we have extended the Galaxy bioinformatics framework to facilitate proteogenomic analysis. Using analysis of whole human saliva as an example, we demonstrate Galaxy’s flexibility through the creation of a modular workflow incorporating both established and customized software tools that improve depth and quality of proteogenomic results. Our customized Galaxy-based software includes automated, batch-mode BLASTP searching and a Peptide Sequence Match Evaluator tool, both useful for evaluating the veracity of putative novel peptide identifications. Our complex workflow (approximately 140 steps) can be easily shared using built-in Galaxy functions, enabling their use and customization by others. Our results provide a blueprint for the establishment of the Galaxy framework as an ideal solution for the emerging field of proteogenomics.
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影响因子：
3.4
作者：
Jagtap, Pratik;McGowan, Thomas;Bandhakavi, Sricharan;Tu, Zheng Jin;Seymour, Sean;Griffin, Timothy J.;Rudney, Joel D.
通讯作者：
Rudney, Joel D.
影响因子：
5.1
作者：
Ivankov DN;Payne SH;Galperin MY;Bonissone S;Pevzner PA;Frishman D
通讯作者：
Frishman D
影响因子：
2.2
作者：
Jacob, Francis;Goldstein, Darlene R.;Heinzelmann-Schwarz, Viola
通讯作者：
Heinzelmann-Schwarz, Viola
影响因子：
5.8
作者：
Blankenberg, Daniel;Johnson, James E.;Nekrutenko, Anton
通讯作者：
Nekrutenko, Anton
影响因子：
12.3
作者：
Fermin, Damian;Allen, Baxter B.;Blackwell, Thomas W.;Menon, Rajasree;Adamski, Marcin;Xu, Yin;Ulintz, Peter;Omenn, Gilbert S.;States, David J.
通讯作者：
States, David J.