Finite-State Semi-Markov Channels for Nanopore Sequencing

TL;DR

This paper introduces a finite-state semi-Markov channel model for nanopore DNA sequencing that captures key distortions, enabling the development of MAP detection algorithms and rate estimation for improved sequencing accuracy.

Contribution

It proposes a novel channel model for nanopore sequencing that accounts for duplications and inter-symbol interference, facilitating future coding scheme development.

Findings

Model effectively captures dominant nanopore distortions

Derives MAP detection algorithms for the proposed channel

Estimates achievable information rates

Abstract

Nanopore sequencing is an emerging DNA sequencing technology that has been proposed for use in DNA storage systems. We propose the noisy nanopore channel model for nanopore sequencing. This model captures duplications, inter-symbol interference, and noisy measurements by concatenating an i.i.d. duplication channel with a finite-state semi-Markov channel. Compared to previous models, this channel models the dominant distortions of the nanopore while remaining tractable. Anticipating future coding schemes, we derive MAP detection algorithms and estimate achievable rates. Given that finite-state semi-Markov channels are a subclass of channels with memory, we conjecture that the achievable rate of the noisy nanopore channel can be optimised using a variation of the generalised Blahut-Arimoto algorithm.