A statistically rigorous test for the identification of parent-fragment pairs in LC-MS datasets.
A statistically rigorous test for the identification of parent-fragment pairs in LC-MS datasets.
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DOI：
10.1021/ac902361f
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发表时间：
2010-03-01
影响因子：
7.4
通讯作者：
Ebbels, Timothy M. D.
中科院分区：
文献类型：
--
作者：
Ipsen, Andreas;Want, Elizabeth J.;Lindon, John C.;Ebbels, Timothy M. D.
通过液相色谱-质谱法进行的非靶向全局代谢分析会产生许多未知化合物的信号，这些信号的识别构成了一个重要的挑战。碰撞诱导解离后的代谢物碎片模式分析提供了一种有价值的鉴定工具，但可能受到不同代谢物的紧密色谱共洗脱的严重阻碍。我们提出了一种新的算法，用于识别相关的亲本片段对，并区分这些信号，由于不相关的化合物。与现有的方法不同，我们的方法通过假设检验来解决这个问题，该假设检验是基于所记录的离子计数的分布的，从而提供了分类问题中所涉及的不确定性的统计上严格的测量。由于技术限制，该测试主要用于低和中等离子计数，高于该值时，检测器饱和会导致记录的离子计数出现实质性偏差。通过将其应用于共洗脱同位素体对和已知的母片段对，证明了检验的有效性，这导致检验统计量与零分布一致。该测试的性能与常用的皮尔逊相关方法进行了比较，发现其明显更好（例如，假阳性率为6.25%，相比之下，对于完全共洗脱离子的相关性值为50%）。由于该算法可用于高质量的化合物，除了代谢数据的分析，我们希望它能方便的分析范围广泛的分析问题的碎片模式。
Untargeted global metabolic profiling by liquid chromato-graphy−mass spectrometry generates numerous signals that are due to unknown compounds and whose identification forms an important challenge. The analysis of metabolite fragmentation patterns, following collision-induced dissociation, provides a valuable tool for identification, but can be severely impeded by close chromatographic coelution of distinct metabolites. We propose a new algorithm for identifying related parent−fragment pairs and for distinguishing these from signals due to unrelated compounds. Unlike existing methods, our approach addresses the problem by means of a hypothesis test that is based on the distribution of the recorded ion counts, and thereby provides a statistically rigorous measure of the uncertainty involved in the classification problem. Because of technological constraints, the test is of primary use at low and intermediate ion counts, above which detector saturation causes substantial bias to the recorded ion count. The validity of the test is demonstrated through its application to pairs of coeluting isotopologues and to known parent−fragment pairs, which results in test statistics consistent with the null distribution. The performance of the test is compared with a commonly used Pearson correlation approach and found to be considerably better (e.g., false positive rate of 6.25%, compared with a value of 50% for the correlation for perfectly coeluting ions). Because the algorithm may be used for the analysis of high-mass compounds in addition to metabolic data, we expect it to facilitate the analysis of fragmentation patterns for a wide range of analytical problems.
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HMDB：人类代谢组数据库。
影响因子：
14.9
作者：
Wishart, David S;Tzur, Dan;Knox, Craig;Eisner, Roman;Guo, An Chi;Young, Nelson;Cheng, Dean;Jewell, Kevin;Arndt, David;Sawhney, Summit;Fung, Chris;Nikolai, Lisa;Lewis, Mike;Coutouly, Marie-Aude;Forsythe, Ian;Tang, Peter;Shrivastava, Savita;Jeroncic, Kevin;Stothard, Paul;Amegbey, Godwin;Block, David;Hau, David D;Wagner, James;Miniaci, Jessica;Clements, Melisa;Gebremedhin, Mulu;Guo, Natalie;Zhang, Ying;Duggan, Gavin E;Macinnis, Glen D;Weljie, Alim M;Dowlatabadi, Reza;Bamforth, Fiona;Clive, Derrick;Greiner, Russ;Li, Liang;Marrie, Tom;Sykes, Brian D;Vogel, Hans J;Querengesser, Lori
通讯作者：
Querengesser, Lori
影响因子：
7.4
作者：
Lommen, Arjen
通讯作者：
Lommen, Arjen
影响因子：
2
作者：
Plumb, Robert S.;Johnson, Kelly A.;Nicholson, Jeremy K.
通讯作者：
Nicholson, Jeremy K.
影响因子：
1.8
作者：
Nicholson, JK;Lindon, JC;Holmes, E
通讯作者：
Holmes, E
影响因子：
2
作者：
Chakraborty, Asish B.;Berger, Scott J.;Gebler, John C.
通讯作者：
Gebler, John C.