A general-purpose baseline estimation algorithm for spectroscopic data
A general-purpose baseline estimation algorithm for spectroscopic data
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DOI：
10.1016/j.aca.2009.10.043
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发表时间：
2010-01-11
影响因子：
6.2
通讯作者：
Rocke, David M.
中科院分区：
文献类型：
--
作者：
Barkauskas, Donald A.;Rocke, David M.
蛋白质组学中使用的许多现代技术--包括核磁共振成像和质谱学--的一个共同特征是，在实验中为每个受试者产生大量数据。然而，从背景噪声中提取信号会带来巨大的挑战。信号提取的一个重要部分是正确识别数据的基线水平。在本文中，我们提出了一种新的基线估计算法(BXR算法)，该算法可以直接应用于不同类型的光谱数据，也可以专门针对不同的技术进行定制。然后，我们展示了如何使算法适应一种特定的技术--基质辅助激光解吸/电离傅立叶变换离子回旋共振质谱仪-作为蛋白质组学中的一种分析工具正在迅速流行起来。最后，我们将该算法与现有的基线估计算法进行了比较，BXR算法计算效率高，对现代应用(包括核磁共振和质谱仪)中出现的单边信号类型具有较强的稳健性，并对现有的基线估计算法进行了改进。它作为R包FTICRMS中的功能基线实施，可从全面R档案网(http://www.r-project.org/))或第一作者处获得。(C)2009爱思唯尔B.V.保留所有权利。
A common feature of many modern technologies used in proteomics - including nuclear magnetic resonance imaging and mass spectrometry - is the generation of large amounts of data for each subject in an experiment. Extracting the signal from the background noise, however, poses significant challenges. One important part of signal extraction is the correct identification of the baseline level of the data. In this article, we propose a new algorithm (the "BXR algorithm") for baseline estimation that can be directly applied to different types of spectroscopic data, but also can be specifically tailored to different technologies. We then show how to adapt the algorithm to a particular technology - matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry - which is rapidly gaining popularity as an analytic tool in proteomics. Finally, we compare the performance of our algorithm to that of existing algorithms for baseline estimation.The BXR algorithm is computationally efficient, robust to the type of one-sided signal that occurs in many modern applications (including NMR and mass spectrometry), and improves on existing baseline estimation algorithms. It is implemented as the function baseline in the R package FTICRMS, available either from the Comprehensive R Archive Network (http://www.r-project.org/) or from the first author. (C) 2009 Elsevier B.V. All rights reserved.