English

PHONI: Streamed Matching Statistics with Multi-Genome References

Data Structures and Algorithms 2021-02-12 v2

Abstract

Computing the matching statistics of patterns with respect to a text is a fundamental task in bioinformatics, but a formidable one when the text is a highly compressed genomic database. Bannai et al. gave an efficient solution for this case, which Rossi et al. recently implemented, but it uses two passes over the patterns and buffers a pointer for each character during the first pass. In this paper, we simplify their solution and make it streaming, at the cost of slowing it down slightly. This means that, first, we can compute the matching statistics of several long patterns (such as whole human chromosomes) in parallel while still using a reasonable amount of RAM; second, we can compute matching statistics online with low latency and thus quickly recognize when a pattern becomes incompressible relative to the database.

Keywords

Cite

@article{arxiv.2011.05610,
  title  = {PHONI: Streamed Matching Statistics with Multi-Genome References},
  author = {Christina Boucher and Travis Gagie and Tomohiro I and Dominik Köppl and Ben Langmead and Giovanni Manzini and Gonzalo Navarro and Alejandro Pacheco and Massimiliano Rossi},
  journal= {arXiv preprint arXiv:2011.05610},
  year   = {2021}
}

Comments

Our code is available at https://github.com/koeppl/phoni

R2 v1 2026-06-23T20:04:27.342Z