A Bayesian approach to the alignment of mass spectra.
A Bayesian approach to the alignment of mass spectra.
复制标题
质谱对齐的贝叶斯方法。
DOI：
10.1093/bioinformatics/btp582
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Reilly,Cavan
中科院分区：
文献类型：
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作者：
Kong,Xiaoxiao;Reilly,Cavan
动机：需要对光谱进行校准，以纠正质谱（MS）中出现的质量-电荷实验变化。大多数基于质谱的蛋白质组学数据分析方法都是两步法，首先确定峰，然后对这些峰进行比对和统计推断。然而，峰识别步骤依赖于感兴趣的蛋白质的先验信息或峰检测模型，这是容易出错的。此外，在简单的峰检测中会丢失许多附加特征，例如峰形状和峰宽度，这些特征对于校正校准步骤中的质量变化具有重要意义。结果：本文提出了一种新的贝叶斯方法来对准全光谱。该方法基于参数化模型，假设谱和对准函数是高斯过程，但对准函数是单调的。我们展示了如何使用期望最大化算法来找到一组对齐函数的后验模式和患者群体的平均谱。对齐后，我们进行测试，同时控制由两个患者群体的绝对平均光谱差确定的峰水平的多次比较引起的误差。联系：cavanr@biostat.umn.edu
Motivation:The need to align spectra to correct for mass-to-charge experimental variation is a problem that arises in mass spectrometry (MS). Most of the MS-based proteomic data analysis methods involve a two-step approach, identify peaks first and then do the alignment and statistical inference on these identified peaks only. However, the peak identification step relies on prior information on the proteins of interest or a peak detection model, which are subject to error. Also numerous additional features such as peak shape and peak width are lost in simple peak detection, and these are informative for correcting mass variation in the alignment step.Results:Here, we present a novel Bayesian approach to align the complete spectra. The approach is based on a parametric model which assumes that the spectrum and alignment function are Gaussian processes, but the alignment function is monotone. We show how to use the expectation–maximization algorithm to find the posterior mode of the set of alignment functions and the mean spectrum for a patient population. After alignment, we conduct tests while controlling for error attributable to multiple comparisons on the level of the peaks identified from the absolute mean spectra difference of two patient populations.Contact:cavanr@biostat.umn.edu