STATISTICAL PRE PROCESSING OF RAW SPECTRA

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 检查复杂多肽混合物的LC-MS/MS原始数据(例如，在主要组织相容性复合体或蛋白质组学中遇到的蛋白质消化中发现的那些)表明，只有一小部分光谱具有足够的强度来提供高质量的产品离子光谱。此外，许多“高质量”的光谱可能是非肽类污染物，不会产生序列信息。如果所有的外来光谱都能被预先识别并从搜索中消除，就可以进行更有效和更快速的搜索。使用多变量方法分析MS/MS统计数据，并包括化学相关的分类器可以提高识别率。用Perl编写了一个新的计算机程序。该程序从每个原始光谱中提取统计信息和暂定部分序列。使用偏最小二乘法对数据进行评估，以计算统计模型。预测得分与实际得分之间的相关性足以消除很大比例的“噪声”频谱。由于哺乳动物蛋白质组的修饰率估计为每个蛋白质约3PTM，因此仅保留具有多肽特征的谱，剩余的未识别谱将是基于相关性的PTM搜索程序的良好候选者。

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. Examining LC-MS/MS raw data of complex peptide mixtures (e.g., those found in major histocompatibility complexes or in protein digests encountered in proteomics) shows that only a fraction of the spectra are of sufficient intensity to give good quality product ion spectra. Moreover many of the "good quality" spectra can be of non-peptidic contaminates and will not yield sequence information. If all the extraneous spectra could be identified and eliminated from the search beforehand, a much more efficient and fast search could be preformed. Analyzing MS/MS statistical data using multivariate methods and including chemically relevant classifiers can improve the discrimination. A new computer program was written using PERL. The program extracts statistical information and tentative partial sequences from each raw spectrum. The data is evaluated to calculate a statistical model using Partial Least Squeres method. The correlation between the predicted score to the actual one is sufficient to eliminate a large percentage of the "noise" spectra. Since the rate of modifications in mamalian proteom is estimated to be about 3 PTM per protein and only spectra with a peptidic signature will be retained, the remaining unidentified spectra will be good candidates for correlation based PTM search program.