2 research outputs found
Fully-Automatic Multiresolution Idealization for Filtered Ion Channel Recordings: Flickering Event Detection
We propose a new model-free segmentation method, JULES, which combines recent
statistical multiresolution techniques with local deconvolution for
idealization of ion channel recordings. The multiresolution criterion takes
into account scales down to the sampling rate enabling the detection of
flickering events, i.e., events on small temporal scales, even below the filter
frequency. For such small scales the deconvolution step allows for a precise
determination of dwell times and, in particular, of amplitude levels, a task
which is not possible with common thresholding methods. This is confirmed
theoretically and in a comprehensive simulation study. In addition, JULES can
be applied as a preprocessing method for a refined hidden Markov analysis. Our
new methodolodgy allows us to show that gramicidin A flickering events have the
same amplitude as the slow gating events. JULES is available as an R function
jules in the package clampSeg
Heterogeneous Idealization of Ion Channel Recordings -- Open Channel Noise
We propose a new model-free segmentation method for idealizing ion channel
recordings. This method is designed to deal with heterogeneity of measurement
errors. This in particular applies to open channel noise which, in general, is
particularly difficult to cope with for model-free approaches. Our methodology
is able to deal with lowpass filtered data which provides a further
computational challenge. To this end we propose a multiresolution testing
approach, combined with local deconvolution to resolve the lowpass filter.
Simulations and statistical theory confirm that the proposed idealization
recovers the underlying signal very accurately at presence of heterogeneous
noise, even when events are shorter than the filter length. The method is
compared to existing approaches in computer experiments and on real data. We
find that it is the only one which allows to identify openings of the PorB
porine at two different temporal scales. An implementation is available as an R
package