Multivariate statistics in analysis of data from the in vitro motility assay
Multivariate statistics in analysis of data from the in vitro motility assay
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DOI：
10.1016/s0003-2697(02)00610-3
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发表时间：
2003-03-15
影响因子：
2.9
通讯作者：
Tågerud, S
中科院分区：
文献类型：
--
作者：
Månsson, A;Tågerud, S
描述了一种新的方法，用于分类的丝作为静止或移动和提取的速度数据在体外平滑肌动蛋白丝滑动。在多元统计分析中，使用四个判别变量对运动和静止细丝进行有效分类。变量是（1）距其起始点的平均细丝距离的两种不同测量，（2）滑动方向的可变性的测量，（3）帧间滑动速度的变异系数（CV）（nu（mean））。在此多元分析的基础上，我们对98%的静止丝和94%的静止丝进行了正确分类。在交叉验证数据集中的移动细丝。尽管交叉验证数据中的平均滑动速度有10倍的变化，但相同的分类函数始终是有用的。对运动细丝的进一步分析表明，理想情况下，平滑滑动的速度应该从nu（平均值）对CV曲线的速度轴上的截距获得。如此获得的速度比如果获得CV < 0.5的所有运动细丝的平均滑动速度高10 - 30%（平均值20 +/-3%; n = 7; p <0.001）。(C)2003 Elsevier Science（美国）。All rights reserved.
A novel approach is described for classification of filaments as stationary or moving and for extraction of velocity data for smooth actin filament sliding in vitro. Moving and stationary filaments were effectively classified using four discriminating variables in a multivariate statistical analysis. The variables were (1) two different measures of the average filament distance from its starting point, (2) a measure of the variability in sliding direction, and (3) the coefficient of variation (CV) of the frame-to-frame sliding velocity (nu(mean)) On the basis of this multivariate analysis we obtained correct classification of 98% of the stationary filaments and 94% of the moving filaments in a cross-validation data set. The same classification functions were useful throughout despite a 10-fold variation in the average sliding velocity in the cross-validation data. Further analysis of motile filaments suggested that the velocity of smooth sliding should, ideally, be obtained from the intercept on the velocity axis of a plot of nu(mean) against CV. The velocity, so obtained, was between 10 and 30% (mean 20 +/- 3%; n = 7; p < 0.00 1) higher than if average sliding velocity was obtained for all moving filaments with CV < 0.5. (C) 2003 Elsevier Science (USA). All rights reserved.