Draber S, Schultze R
Institut für Angewandte Physik, Universität Kiel, Germany.
Biophys J. 1994 Oct;67(4):1404-13. doi: 10.1016/S0006-3495(94)80614-9.
Detection algorithms are widely used for the analysis of single-channel data because they remove the background noise from the measured current signal and reconstruct the noise-free time series. Standard detection algorithms assume channels switching only between zero and full conductance. Many types of channels, however, show subconductance levels. A new detection algorithm for data containing sublevels, the so-called sublevel Hinkley-detector (SHD), calculates several test values in parallel, one for each possible jump. The velocity of increase has a maximum for the correct jump. This feature is used to detect the jump and to diagnose the new level of current. Because patch-clamp data are always filtered by an antialiasing low-pass filter before sampling, the algorithm is supplemented by a special diagnosis phase accounting for the distortion of the originally rectangular jumps. Along with the reconstructed (noise-free) time series the SHD also gives a matrix of the transition counts between the levels. This matrix is a useful statistical tool for the decision whether the observed channel(s) have in fact a subconductance conformation or if there are simply several channels of different conductivity contained within the patch.
检测算法被广泛用于单通道数据的分析,因为它们能从测量的电流信号中去除背景噪声,并重建无噪声的时间序列。标准检测算法假设通道仅在零电导和全电导之间切换。然而,许多类型的通道会显示亚电导水平。一种针对包含亚水平数据的新检测算法,即所谓的亚水平欣克利检测器(SHD),会并行计算几个测试值,每个可能的跃变对应一个测试值。对于正确的跃变,增加速度有一个最大值。此特征用于检测跃变并诊断电流的新水平。由于膜片钳数据在采样前总是通过抗混叠低通滤波器进行滤波,该算法通过一个特殊的诊断阶段进行补充,该阶段考虑了原本矩形跃变的失真。除了重建的(无噪声)时间序列外,SHD还给出了各水平之间跃迁计数的矩阵。该矩阵是一个有用的统计工具,可用于判断观察到的通道实际上是否具有亚电导构象,或者膜片中是否仅仅包含几个不同电导率的通道。