Improving large-scale proteomics by clustering of mass spectrometry data
Improving large-scale proteomics by clustering of mass spectrometry data
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DOI：
10.1002/pmic.200300652
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发表时间：
2004-04-01
期刊：
影响因子：
3.4
通讯作者：
Admon, A
中科院分区：
文献类型：
--
作者：
Beer, I;Barnea, E;Admon, A
串联质谱（MS/MS）与液相色谱（LC）结合，是分析和比较复杂蛋白质和肽混合物的有力工具。然而，该过程产生的大量数据非常复杂，难以分析。我们展示了如何从多个LC-MS/MS运行的相似光谱的聚类可以帮助数据管理和改善复杂肽混合物的分析。频谱聚类的主要作用是将大量的数据减少到可管理的大小。因此，分析时间更短，可以存储更多数据以供进一步分析。此外，光谱质量的改善允许识别更多的肽与更大的信心，复杂的肽混合物的比较是方便的，整个蛋白质组学项目以简洁的形式呈现。Pep-Miner是一种高级软件工具，可以实现这些基于集群的应用程序。它在涉及肺癌细胞和各种其他细胞类型的几个比较蛋白质组学项目中证明是有用的。在其中一个项目中，Pep-Miner将517 000个光谱减少到20 900个簇，并鉴定了来自830种蛋白质的2518种肽。聚类和识别在IBM Thinkpad T23计算机（笔记本电脑）上持续了不到两个小时。Pep-Miner的独特性质使其成为大规模鸟枪蛋白质组学项目的非常有用的工具。
Tandem mass spectrometry (MS/MS), coupled with liquid chromatography (LC), is a powerful tool for the analysis and comparison of complex protein and peptide mixtures. However, the extremely large amounts of data that result from the process are very complex and difficult to analyze. We show how the clustering of similar spectra from multiple LC-MS/MS runs can help in data management and improve the analysis of complex peptide mixtures. The major effect of spectrum clustering is the reduction of the huge amounts of data to a manageable size. As a result, analysis time is shorter and more data can be stored for further analysis. Furthermore, spectrum quality improvement allows the identification of more peptides with greater confidence, the comparison of complex peptide mixtures is facilitated, and the entire proteomics project is presented in concise form. Pep-Miner is an advanced software tool that implements these clustering-based applications. It proved useful in several comparative proteomics projects involving lung cancer cells and various other cell types. In one of these projects, Pep-Miner reduced 517 000 spectra to 20 900 clusters and identified 2518 peptides derived from 830 proteins. Clustering and identification lasted less than two hours on an IBM Thinkpad T23 computer (laptop). Pep-Miner's unique properties make it a very useful tool for large-scale shotgun proteomics projects.