HyperXtract: Strategic Platform for Optimizing High-Bandwidth Nanopore Data Extraction Performance

High-bandwidth amplifiers that offer measurement capabilities on the submicrosecond scale to resonate with short-lived events have recently gained tremendous traction in solid-state nanopore (SSN) sensing. High acquisition rate data collection is a hallmark of such measurements, leading to oversized files. Such experimental needs warrant high-performance analysis platforms that can analyze large files in a reasonable time frame. This study introduces a new platform (coined HyperXtract, HX) that supersedes the capabilities of other readily available SSN analysis platforms. HX is benchmarked against its predecessor, NanoPlex (NP), which has demonstrated superior performance characteristics against other readily available SSN event extraction platforms. For example, a 1000 s-long file acquired at 40 MHz only takes <50 s with HX, while NP takes >45× more time for the event extraction. The salient features underpinning the superior performance metrics of HX include using MEX functions, memory mapping, preallocation of storage vectors, optimizing standard functions, and event-free baseline segment isolation to determine the event detection coefficient. The ability to extract events <5% of the acquisition time places HX to assist with near real-time decision-making in challenging high-bandwidth experiments. These code optimizations allow HX to outperform NP even while using less powerful computers.