Riessner T, Woelk F, Abshagen-Keunecke M, Caliebe A, Hansen U-P
Center of Biochemistry and Molecular Biology of the Christian-Albrechts-Universität, Leibnizstr. 11, 24098 Kiel, Germany.
J Membr Biol. 2002 Sep 15;189(2):105-18. doi: 10.1007/s00232-002-1011-y.
The algorithm proposed here for automatic level detection in noisy time series of patch-clamp current is based on the detection of jump-free sections in the time series. The detector moves along the time series and uses a chi(2) test for the detection of jumps. When a jump is detected, the mean value, the variance and the length of the preceding jump-free section are stored. A Student's t-test was employed for the assignment of detected jump-free sections to discrete levels of the Markov model and for rejection of all sections with multiple assignments. The choice of the two significance levels is based on a 3-D diagram displaying the average number of detected levels from several time series vs. the significance levels of jump detection and of level assignment. The correct one is selected out of several plateaus with integer number of levels by means of the criterion of minimum scatter or other plausibility considerations. The test has been applied to simulated data obtained from a 2-state model and a 5-state aggregated Markov model, and the influences of SNR and of gating frequency are shown. Finally, the performance of the level detector is compared with a fit-by-eye and with a fit of the amplitude histogram by a sum of gaussians. At high noise, the fit of amplitude histograms failed, whereas the other two approaches were about equal.
这里提出的用于在膜片钳电流的噪声时间序列中自动进行电平检测的算法,是基于对时间序列中无跳跃段的检测。检测器沿着时间序列移动,并使用卡方检验来检测跳跃。当检测到一个跳跃时,前一个无跳跃段的平均值、方差和长度就会被存储起来。采用学生t检验将检测到的无跳跃段分配到马尔可夫模型的离散电平,并剔除所有有多重分配的段。两个显著性水平的选择基于一个三维图,该图显示了来自几个时间序列的检测到的电平平均数与跳跃检测和电平分配的显著性水平的关系。通过最小散射标准或其他合理性考虑,从具有整数个电平的几个平台中选择正确的一个。该测试已应用于从二态模型和五态聚合马尔可夫模型获得的模拟数据,并展示了信噪比和门控频率的影响。最后,将电平检测器的性能与凭肉眼拟合以及用高斯和拟合幅度直方图的方法进行了比较。在高噪声情况下,幅度直方图的拟合失败,而其他两种方法大致相当。