Nanopore Data Analysis: Baseline Construction and Abrupt Change-Based Multilevel Fitting

Solid-state nanopore technology delivers single-molecule resolution information, and the quality of deliverables hinges on capability analysis platform to extract maximum possible events fit them appropriately. In this work, we present an with four baseline fitting methods adaptive a wide range traces (including those step or abrupt changes where pre-existing platforms fail) maximize extractable (2× improvement in some cases) multilevel event capability. The methods, increasing order robustness computational cost, include arithmetic mean, linear fit, Gaussian smoothing, smoothing regressed mixing. performance was tested ultra-stable vigorously fluctuating current profiles, count increased prominently for profiles. Turning points were clustered using dbscan method, followed by segmentation into preliminary levels based signal level, which then iteratively refined deduce final event. Finally, show utility clustering DNA data analysis, assessment protein translocation