Finite-State Semi-Markov Channels for Nanopore Sequencing
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.
Cite
@article{arxiv.2205.04187,
title = {Finite-State Semi-Markov Channels for Nanopore Sequencing},
author = {Brendon McBain and Emanuele Viterbo and James Saunderson},
journal= {arXiv preprint arXiv:2205.04187},
year = {2022}
}
Comments
6 pages. 4 figures. To appear in the Proceedings of the 2022 IEEE International Symposium on Information Theory (ISIT)