A new level detector for ion channel analysis.
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.
Riessner
T
T
Center of Biochemistry and Molecular Biology of the Christian-Albrechts-Universität, Leibnizstr. 11, 24098 Kiel, Germany.
Woelk
F
F
Abshagen-Keunecke
M
M
Caliebe
A
A
Hansen
U-P
UP
D000465:Algorithms; D003198:Computer Simulation; D004594:Electrophysiology / Q000379:methods; D056890:Eukaryota / Q000502:physiology; D015640:Ion Channel Gating / Q000502:physiology; D007473:Ion Channels / Q000502:physiology*; D008390:Markov Chains; D008564:Membrane Potentials / Q000502:physiology; D008954:Models, Biological; D015233:Models, Statistical; D016011:Normal Distribution; D018408:Patch-Clamp Techniques / Q000379:methods*; D011786:Quality Control; D012680:Sensitivity and Specificity; D013269:Stochastic Processes
D007473:Ion Channels