SOFTWARE FOR MASS SPECTRAL DATA CONVERSION / AUTOMATIC PROTEOMIC ANALYSIS

质谱数据转换/自动蛋白质组分析软件

• 批准号: 7722964
• 负责人: Catherine E. Costello
• 金额: $ 0.52万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7722964
• 关键词: Algorithms; Archives; Boston; Computer Retrieval of Information on Scientific Projects Database; Computer software; Data; Data Analyses; Data Files; Data Set; Databases; E2F Transcription Factor 1; Extensible Markup Language; Fingerprint; Funding; Grant; Hemoglobin; Housing; Human; Imagery; Institutes; Institution; Libraries; Link; Linux; Manufacturer Name; Mass Spectrum Analysis; Methodology; Modeling; Numbers; Online Systems; Operative Surgical Procedures; Peptide Mapping; Peptides; Performance; Pliability; Probability; Process; Proteins; Proteomics; Relative (related person); Research; Research Personnel; Resources; Running; Sampling; Score; Sodium Dodecyl Sulfate-PAGE; Source; Specific qualifier value; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Statistical Models; Systems Biology; Testing; United States National Institutes of Health; Universities; Visual; Water; Writing; base; comparative; computerized data processing; graphical user interface; instrument; instrumentation; programs; tool; user-friendly; web based interface

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. With a multitude of different MS instrumentation and data analysis software platforms available for MS and proteomics, it becomes difficult to manipulate and manage various data sets. We have created a software application that will allow the conversion of processed MS data files obtained on a variety of instruments into several common formats accepted by different software applications. We have further developed the program to add support for the mzXML format (Pedroli et al., 2004) and incorporate a front end interface which may be linked to several web based database searching engines including Mascot, ProteinProspector and BUPID (a peptide mass fingerprinting program based on a log-likelihood ratio model developed here at BUSM) (Tong et al., 2005). The data processing software was developed using Microsoft Visual Basic 6.0. To add support for mzXML format, we used MSXML 4.0 as an XML parser and built a visual C++ library to decode Base64 encoded peak list data in the mzXML file. Other supported data formats are intermediate files converted from raw data files using software from the manufacturers: LC MS/MS data is processed with Analyst QS (ABI/Sciex), MassLynx/PLGS2.1 (Waters); and MALDI MS data with MOverZ (Proteometrics LLC); and FTMS data with BUDA (O'Connor, http://www.bumc.bu.edu/FTMS). The BUPID program was developed in C under Linux and made accessible to the main program through a CGI based web interface. The shell data conversion program was written to implement a user friendly GUI interface which may be operated in an unattended batch processing mode. Testing of the program was performed on existing MALDI-TOF MS, MALDI-FT MS and LC MS/MS data sets obtained in house. The program allowed the conversion of large volumes of data obtained on different instruments to the formats of several commercially and publicly available search engines. Files were then submitted for protein identification to the search engines with the search settings specified by the user. For a batch of files, the search setting only needs to be specified once, thus allowing unattended operation. Results files are automatically saved in HTML format and can then be viewed directly inside the program. Our recent implementation of the mzXML format introduced by the Institute for Systems Biology affords the benefits of a common data format for summation of results obtained on different MS platforms, comparative analysis of MS methodology and archiving of data such that it may be analyzed at a later date in-house or at a different facility. The software provides an easy-to-use graphical interface for automatic MS data conversion and database searching. It can also be easily be expanded for more MS data types and linked to more database search engines. The new search algorithm Boston University Protein Identifier (BUPID) provides a robust and accurate statistical model for protein identification using MS data. The algorithm offers a number of new features: 1. Using log-likelihood ratio as scoring function, the algorithm can best distinguish correctly assigned peptides from incorrect assignments. 2. Matching peaks with a background-dependent threshold offers more flexibility and accuracy than the traditional mass window. 3. The statistical model provides similar or better results with comparison to conventional database search engines. We use log-likelihood ratio to calculate the probability that a protein is present in the sample. The model distinguishes two hypotheses ? H0: That a set of peaks in the spectrum is generated by the random background; and HA: That the same set of peaks is generated by peptides corresponding to a specific protein. A peak is included in the set if the probability that it is produced by the protein is more significant than that it is otherwise produced by the random background. Final results are ranked by the E-value of their probability score using the sequence information of the protein. We have compared the performance of the BUPID server and several other public web-based database search engines. Peptide map data sets were obtained from existing ongoing projects. BUPID database search results had on average 27% more true positives in top 10 predictions, with comparison to MASCOT results. Within the top 100 predictions, BUPID showed 27% more true positives as compared to MASCOT. In addition, BUPID was able to find all five human hemoglobin proteins in 6 cases within top 20. MASCOT succeeded in one case. When using peaks with higher than 5% relative intensity, the spreads are 28% and 24% within top 10 and 100 predictions, respectively. With another MALDI data set (transcription factor E2F1 protein purified and separated on 1D SDS PAGE), all five search engines pulled out similar results. BUPID also provides various data visualizations tools that are found useful by many users, including combined view of a protein mixture, mass spectrum of shared or similar peptides in different proteins, etc. A typical BUPID run takes 2~3 minutes on a Pentium IV PC.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 随着大量不同的MS仪器和数据分析软件平台可用于MS和蛋白质组学，它变得难以操纵和管理各种数据集。我们已经创建了一个软件应用程序，该软件应用程序将允许将在各种仪器上获得的经处理的MS数据文件转换为不同软件应用程序接受的几种常见格式。我们已经进一步开发了该程序，以添加对mzXML格式的支持（Pedroli等人，2004）并结合前端接口，该前端接口可以链接到几个基于网络的数据库搜索引擎，包括Mascot、ProteinProspector和BUPID（基于在BUSM开发的对数似然比模型的肽质量指纹程序）（Tong等人，2005年）。数据处理软件采用Microsoft Visual Basic 6.0开发。为了增加对mzXML格式的支持，我们使用MSXML 4.0作为XML解析器，并构建了一个Visual C++库来解码mzXML文件中Base64编码的峰列表数据。其他支持的数据格式为使用生产商软件从原始数据文件转换的中间文件：LC MS/MS数据使用Analyst QS（ABI/Sciex）、MassLynx/PLGS 2.1（沃茨）处理; MALDI MS数据使用MOverZ（Proteometrics LLC）处理; FTMS数据使用BUDA（奥康纳，http：//www.bumc.bu.edu/FTMS）处理。BUPID程序是在Linux下用C语言开发的，通过基于CGI的Web界面可访问主程序。 编写外壳数据转换程序以实现用户友好的GUI界面，该界面可以在无人值守的批处理模式下操作。对内部获得的现有MALDI-TOF MS、MALDI-FT MS和LC MS/MS数据集进行程序检测。该方案允许将通过不同仪器获得的大量数据转换为若干商业和公开搜索引擎的格式。然后将文件提交给具有用户指定的搜索设置的搜索引擎进行蛋白质鉴定。对于一批文件，搜索设置只需要指定一次，从而允许无人值守操作。结果文件自动保存为HTML格式，然后可以直接在程序中查看。我们最近实施的系统生物学研究所推出的mzXML格式提供了一个共同的数据格式的好处，在不同的MS平台上获得的结果汇总，MS方法和数据存档的比较分析，以便它可以在以后的日期在内部或在不同的设施进行分析。该软件提供了一个易于使用的图形界面，用于自动MS数据转换和数据库搜索。它也可以很容易地扩展为更多的MS数据类型，并链接到更多的数据库搜索引擎。 新的搜索算法Boston University Protein Identifier（BUPID）为使用MS数据进行蛋白质鉴定提供了一个强大而准确的统计模型。该算法提供了一些新的功能：1。使用对数似然比作为评分函数，该算法可以最好地区分正确分配的肽与不正确的分配。2.与传统的质量窗口相比，使用背景相关阈值匹配峰提供了更高的灵活性和准确性。3.与传统的数据库搜索引擎相比，统计模型提供了类似或更好的结果。我们使用对数似然比来计算样本中存在蛋白质的概率。该模型区分两个假设？第0阶段：光谱中的一组峰由随机背景产生; HA：同一组峰由对应于特定蛋白质的肽产生。如果由蛋白质产生的峰的概率比由随机背景产生的峰的概率更显著，则将该峰包括在该组中。使用蛋白质的序列信息，通过其概率得分的E值对最终结果进行排名。我们比较了BUPID服务器和其他几个公共的基于Web的数据库搜索引擎的性能。肽图谱数据集从现有的正在进行的项目中获得。 与MASCOT结果相比，BUPID数据库搜索结果在前10名预测中平均多出27%的真阳性。在前100个预测中，BUPID比MASCOT多出27%的真阳性。此外，BUPID能够在前20名中的6个病例中找到所有5种人类血红蛋白。马斯科特在一个案例中取得了成功。当使用相对强度高于5%的峰时，在前10和100个预测中的扩展分别为28%和24%。用另一个MALDI数据集（在1D SDS PAGE上纯化和分离的转录因子E2 F1蛋白），所有五个搜索引擎都得到了类似的结果。BUPID还提供了各种数据可视化工具，许多用户发现这些工具很有用，包括蛋白质混合物的组合视图，不同蛋白质中共享或相似肽的质谱等。