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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >Proteomic Cinderella: Customized analysis of bulky MS/MS data in one night
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Proteomic Cinderella: Customized analysis of bulky MS/MS data in one night

机译：蛋白质组学灰姑娘：在一晚的笨重MS / MS数据定制分析

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Proteomic challenges, stirred up by the advent of high-throughput technologies, produce large amount of MS data. Nowadays, the routine manual search does not satisfy the "speed" of modern science any longer. In our work, the necessity of single-thread analysis of bulky data emerged during interpretation of HepG2 proteome profiling results for proteoforms searching. We compared the contribution of each of the eight search engines (X!Tandem, MS-GF+, MS Amanda, MyriMatch, Comet, Tide, Andromeda, and OMSSA) integrated in an open-source graphical user interface SearchGUl (http://searchgui.googlecode.com) into total result of proteoforms identification and optimized set of engines working simultaneously. We also ocompared the results of our search combination with Mascot results using protein kit UPS2, containing 48 human proteins. We selected combination of X!Tandem, MS-GF+ and OMMSA as the most time-efficient and productive combination of search. We added homemade java-script to automatize pipeline from file picking to report generation. These settings resulted in rise of the efficiency of our customized pipeline unobtainable by manual scouting: the analysis of 192 files searched against human proteome (42153 entries) downloaded from UniProt took 11 h.
机译：蛋白质组学挑战，通过高通量技术的出现激起，产生大量MS数据。如今，常规手动搜索不再满足现代科学的“速度”。在我们的工作中，在蛋白质形式搜索的HepG2蛋蛋白质组分析结果的解释过程中出现了庞大数据的单线程分析的必要性。我们比较了八个搜索引擎中的每一个的贡献（x！tandem，ms-gf +，ms Amanda，my修剪，彗星，潮汐，andromeda和omssa）集成在开源图形用户界面searchgul（http：// searchgui .GoogleCode.com）进入蛋白质形式识别和同时工作的优化发动机的结果。我们还将搜索结合的结果与含有48人蛋白质的蛋白质套件UPS2复制了与吉祥物结果。我们选择了X！Tandem，MS-GF +和OMMSA的组合，作为最常数效率和富有成效的搜索组合。我们添加了自制的Java脚本来自动化管道从文件拣选到报告生成。这些设置导致了通过手动侦察所无能为力的定制管道的效率：192张从Uniprot下载的人蛋白质组（42153条目）的分析需要11小时。

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