Aligning extracted LC-MS peak lists via density maximization
Aligning extracted LC-MS peak lists via density maximization
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DOI：
10.1007/s11306-011-0389-x
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发表时间：
2012-06-01
期刊：
影响因子：
3.6
通讯作者：
Yang, Zheng Rong
中科院分区：
文献类型：
--
作者：
Perera, Venura;Zabala, Marta De Torres;Yang, Zheng Rong
质谱灵敏度和质量准确度的快速改进与改进的液相色谱分离技术相结合，可以获得高通量代谢组学数据，为了解生物过程提供了极好的机会。虽然光谱去卷积软件可以识别离散质量及其相关的同位素和加合物，但代谢组学方法在许多统计分析中的实用性，如识别差异丰富的离子，在很大程度上取决于数据质量和鲁棒性，特别是在多个生物复制品中比对特征的准确性。我们已经开发了一种新的算法，使用密度最大化的特征对齐。而不是一个贪婪的迭代，因此本地，合并策略，这已被广泛应用于文献和商业应用中，我们应用一个全球性的合并策略，以提高比对质量。使用模拟和真实的数据，我们证明了我们的新算法提供了高地图（例如色谱图）覆盖率，这对于高度复制的生物数据集的非靶向比较代谢物分析至关重要。
Rapid improvements in mass spectrometry sensitivity and mass accuracy combined with improved liquid chromatography separation technologies allow acquisition of high throughput metabolomics data, providing an excellent opportunity to understand biological processes. While spectral deconvolution software can identify discrete masses and their associated isotopes and adducts, the utility of metabolomic approaches for many statistical analyses such as identifying differentially abundant ions depends heavily on data quality and robustness, especially, the accuracy of aligning features across multiple biological replicates. We have developed a novel algorithm for feature alignment using density maximization. Instead of a greedy iterative, hence local, merging strategy, which has been widely used in the literature and in commercial applications, we apply a global merging strategy to improve alignment quality. Using both simulated and real data, we demonstrate that our new algorithm provides high map (e.g. chromatogram) coverage, which is critically important for non-targeted comparative metabolite profiling of highly replicated biological datasets.