Although nanopore as a single-molecule sensing platform has proven its potential in various applications, data analysis of nanopores remains challenging. Herein, we introduce a method with increased accuracy in nanopore analysis based on the central limit theorem (CLT). An optimal voltage used in detection is determined from the standard deviations of blockage currents and time constants at various voltage biases. Compared with the conventional data analysis method, blockage signals processed with the CLT result in more concentrated distributions of blockage currents and durations. It allows fitting a Gaussian to the duration histogram and avoids the influence of bin sizes on time constants in duration analysis. The proposed method is further validated by applying it to detect isolated microRNAs with solid-state nanopores. Under the optimal voltage, different nucleic acids present in the isolation process are translocated through the nanopore. By processing the event signals with the CLT, all the nucleic acids including the microRNA are well differentiated. The method proposed here should also be applicable for sensing other biomolecules with the solid-state nanopores.
Keywords: central limit theorem; microRNA; molecule sensing; solid-state nanopore; standard deviation.