Translocation of DNA through a silicon nanopore with an applied voltage bias causes the ionic current signal to spike
sharply downward as molecules block the flow of ions through the pore. Proper processing of the sampled signal is
paramount in obtaining accurate translocation kinetics from the negative peaks, but manual analysis is time-consuming.
Here, an algorithm is reported that automates the process. It imports the signal from a tab-delimited text file,
automatically zero-baselines, filters noise, detects negative peaks, and estimates each peak's start and end time. The
imported signal is processed using a zero-overlap sampling window. Peaks are detected by comparison of the window's
standard deviation to a threshold standard deviation in addition to a comparison against a peak magnitude threshold.
Zero-baselining and noise removal is accomplished through calculation of the mean of non-peak window values. The
start and end times of a peak are approximated by checking where the signal becomes positive on either side of the peak.
The program then stores the magnitude, sample number, approximate start time, and approximate end time of each peak
in a matrix. All these tasks are automatically done by the program, requiring only the following initial input from the
user: window size, file path to sampled signal data file, standard deviation threshold, peak magnitude threshold, and
sampling frequency of the sampled signal. Trials with signals from an 11-micron pore sampled at 100 kHz for 30
seconds yielded a high rate of successful peak detection with a magnitude threshold of 600, a standard deviation
threshold of 1.25, and a window size of 100.