Orthogonality measurements for multidimensional chromatography in three and higher dimensional separations.
Orthogonality measurements for multidimensional chromatography in three and higher dimensional separations.
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DOI：
10.1016/j.chroma.2017.06.036
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发表时间：
2017-11-10
期刊：
影响因子：
--
通讯作者：
Davis JM
中科院分区：
文献类型：
--
作者：
Schure MR;Davis JM
三维和更高维分离的可分辨性度量（OM）被提出作为先前开发的OM的扩展，其被用于评估二维（2D）分离的区域利用率。这些OM包括相关系数，维数，信息论度量和凸壳度量。在这些情况中的许多情况下，存在较低维度的子空间度量并且可以容易地计算。这些指标用于解释先前生成的实验数据。实验数据集来自Gilar的肽数据，现在修改为三维（3D），以及来自摩尔和乔根森的全面3D色谱图。具有25个可识别的3D体积元素或峰的摩尔和乔根森色谱图在所有维度上显示出良好的正交性值。然而，基于3D空间的离散化的OM随着分箱参数的变化而显著变化。此示例强调了在更高维度中将大量保留时间作为数据点的重要性，特别是对于使用离散化的方法。Gilar数据在以前的研究中通过7个一维分离配对产生了21个2D数据集，重新解释产生了35个3D数据集。这些数据集显示了许多有趣的性质，其中之一是低维子空间的几何和调和平均值（即，2D）OM与更高维（即，3D）OM。使用OM对Gilar 3D数据集的空间利用率进行排名，具有最大和最小OM的数据集的保留时间以图表形式呈现。讨论了高维技术的正交性，重点是色谱分离中的分子多样性。在信息论的工作中，在以前的正交性研究中发现了一个不一致的地方，使用的二维度量通常被标识为%O。提出了一种新的度量选择，扩展到更高的维度，其特征在于有序和随机保留时间的混合，并应用于实验数据集。在2D中，新的度量总是等于或超过原始度量。然而，结果从原来的和新的方法。
Orthogonality metrics (OMs) for three and higher dimensional separations are proposed as extensions of previously developed OMs, which were used to evaluate the zone utilization of two-dimensional (2D) separations. These OMs include correlation coefficients, dimensionality, information theory metrics and convex-hull metrics. In a number of these cases, lower dimensional subspace metrics exist and can be readily calculated. The metrics are used to interpret previously generated experimental data. The experimental datasets are derived from Gilar’s peptide data, now modified to be three dimensional (3D), and a comprehensive 3D chromatogram from Moore and Jorgenson. The Moore and Jorgenson chromatogram, which has 25 identifiable 3D volume elements or peaks, displayed good orthogonality values over all dimensions. However, OMs based on discretization of the 3D space changed substantially with changes in binning parameters. This example highlights the importance in higher dimensions of having an abundant number of retention times as data points, especially for methods that use discretization. The Gilar data, which in a previous study produced 21 2D datasets by the pairing of 7 one-dimensional separations, was reinterpreted to produce 35 3D datasets. These datasets show a number of interesting properties, one of which is that geometric and harmonic means of lower dimensional subspace (i.e., 2D) OMs correlate well with the higher dimensional (i.e., 3D) OMs. The space utilization of the Gilar 3D datasets was ranked using OMs, with the retention times of the datasets having the largest and smallest OMs presented as graphs. A discussion concerning the orthogonality of higher dimensional techniques is given with emphasis on molecular diversity in chromatographic separations. In the information theory work, an inconsistency is found in previous studies of orthogonality using the 2D metric often identified as %O. A new choice of metric is proposed, extended to higher dimensions, characterized by mixes of ordered and random retention times, and applied to the experimental datasets. In 2D, the new metric always equals or exceeds the original one. However, results from both the original and new methods are given.
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