XCMS: Processing mass spectrometry data for metabolite profiling using Nonlinear peak alignment, matching, and identification
XCMS: Processing mass spectrometry data for metabolite profiling using Nonlinear peak alignment, matching, and identification
复制标题
DOI：
10.1021/ac051437y
复制
发表时间：
2006-02-01
影响因子：
7.4
通讯作者：
Siuzdak, G
中科院分区：
文献类型：
--
作者：
Smith, CA;Want, EJ;Siuzdak, G
生物标志物发现、酶底物分配、药物活性/特异性测定和基础代谢研究中的代谢物分析需要新的数据预处理方法来将特定代谢物与其生物来源相关联。在这里，我们介绍了一种基于LC/MS的数据分析方法，XCMS，它结合了新的非线性保留时间对齐，匹配过滤，峰检测和峰匹配。在不使用内标物的情况下，该方法动态地识别数百种内源性代谢物用作标准品，计算每个样品的非线性保留时间校正曲线。保留时间校正后，直接比较相对代谢物离子强度，以鉴别特定内源性代谢物（如潜在生物标志物）的变化。该软件证明使用数据集从以前报道的酶敲除研究和大规模的血浆样本研究。XCMS可以在http：//www.example.com的开源许可下免费获得。metlin.scripps.edu/download/
Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http:// metlin.scripps.edu/download/.