Self-Calibrated Warping for Mass Spectra Alignment

被引:22
作者
He, Q. Peter [1 ]
Wang, Jin [2 ]
Mobley, James A. [3 ]
Richman, Joshua [4 ]
Grizzle, William E. [5 ]
机构
[1] Tuskegee Univ, Dept Chem Engn, Tuskegee, AL 36088 USA
[2] Auburn Univ, Dept Chem Engn, Auburn, AL 36849 USA
[3] Univ Alabama Birmingham, Dept Surg, Birmingham, AL 35294 USA
[4] Univ Alabama Birmingham, Div Prevent Med, Birmingham, AL 35294 USA
[5] Univ Alabama Birmingham, Dept Pathol, Birmingham, AL 35294 USA
来源
CANCER INFORMATICS | 2011年 / 10卷
基金
美国国家科学基金会;
关键词
mass spectrometry; alignment; warping; peak detection; feature extraction; data preprocessing; proteomics;
D O I
10.4137/CIN.S6358
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
With recent advances in mass spectrometry (MS) technologies, it is now possible to study protein profiles over a wide range of molecular weights in small biological specimens. However, MS spectra are usually not aligned or synchronized between samples. To ensure the consistency of the subsequent analysis, spectrum alignment is necessary to align the spectra such that the same biological entity would show up at the same m/z value for different samples. Although a variety of alignment algorithms have been proposed in the past, most of them are developed based on chromatographic data and do not address some of the unique characteristics of the serum or other body fluid MS data. In this work, we propose a self-calibrated warping (SCW) algorithm to address some of the challenges associated with serum MS data alignment. In addition, we compare the proposed algorithm with five existing representative alignment methods using a clinical surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) data set.
引用
收藏
页码:65 / 82
页数:18
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