Distributions-per-level: a means of testing level detectors and models of patch-clamp data.
Level or jump detectors generate the reconstructed time series from a noisy record of patch-clamp current. The reconstructed time series is used to create dwell-time histograms for the kinetic analysis of the Markov model of the investigated ion channel. It is shown here that some additional lines in the software of such a detector can provide a powerful new means of patch-clamp analysis. For each current level that can be recognized by the detector, an array is declared. The new software assigns every data point of the original time series to the array that belongs to the actual state of the detector. From the data sets in these arrays distributions-per-level are generated. Simulated and experimental time series analyzed by Hinkley detectors are used to demonstrate the benefits of these distributions-per-level. First, they can serve as a test of the reliability of jump and level detectors. Second, they can reveal beta distributions as resulting from fast gating that would usually be hidden in the overall amplitude histogram. Probably the most valuable feature is that the malfunctions of the Hinkley detectors turn out to depend on the Markov model of the ion channel. Thus, the errors revealed by the distributions-per-level can be used to distinguish between different putative Markov models of the measured time series.
Schröder
I
I
Center of Biochemistry and Molecular Biology, Leibnizstr. 11, 24098 Kiel, Germany.
Huth
T
T
Suitchmezian
V
V
Jarosik
J
J
Schnell
S
S
Hansen
U P
UP
D000465:Algorithms; D003198:Computer Simulation; D004056:Differential Threshold / 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; D018408:Patch-Clamp Techniques / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013269:Stochastic Processes
D007473:Ion Channels