One Step Forward for Reducing False Positive and False Negative Compound Identifications from Mass Spectrometry Metabolomics Data: New Algorithms for Constructing Extracted Ion Chromatograms and Detecting Chromatographic Peaks
One Step Forward for Reducing False Positive and False Negative Compound Identifications from Mass Spectrometry Metabolomics Data: New Algorithms for Constructing Extracted Ion Chromatograms and Detecting Chromatographic Peaks
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DOI：
10.1021/acs.analchem.7b00947
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发表时间：
2017-09-05
影响因子：
7.4
通讯作者：
Du, Xiuxia
中科院分区：
文献类型：
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作者：
Myers, Owen D.;Sumner, Susan J.;Du, Xiuxia
从提取的离子色谱（EIC）中检测到的假阳性和假阴性峰是现有的预处理非靶向液体或气相色谱质谱代谢组学数据的软件包面临的一个紧迫问题，因为它们可能在下游转化为虚假或缺失的化合物鉴定。我们开发了新的算法来进行EIC的顺序构建和EIC峰的检测。我们将新算法与两个流行的软件包XCMS和MZmine 2进行比较，并提供证据表明这些新算法检测到的误报明显减少。对于已知存在于数据中的化合物的检测，新算法的表现至少与XCMS和MZmine 2一样好。此外，我们提供的证据表明，在构建EICs的过程中，m/z的质量公差比ppm的质量公差更受青睐。质量容差参数在EIC的构建过程中起着至关重要的作用，对EIC峰的检测有很大的影响。
False positive and false negative peaks detected from extracted ion chromatograms (EIC) are an urgent problem with existing software packages that preprocess untargeted liquid or gas chromatography mass spectrometry metabolomics data because they can translate downstream into spurious or missing compound identifications. We have developed new algorithms that carry out the sequential construction of EICs and detection of EIC peaks. We compare the new algorithms to two popular software packages XCMS and MZmine 2 and present evidence that these new algorithms detect significantly fewer false positives. Regarding the detection of compounds known to be present in the data, the new algorithms perform at least as well as XCMS and MZmine 2. Furthermore, we present evidence that mass tolerance in m/z should be favored rather than mass tolerance in ppm in the process of constructing EICs. The mass tolerance parameter plays a critical role in the EIC construction process and can have immense impact on the detection of EIC peaks.