PHONI: Streamed Matching Statistics with Multi-Genome References
Christina Boucher, Travis Gagie, Tomohiro I, Dominik Köppl,
Ben Langmead, Giovanni Manzini, Gonzalo Navarro, Alejandro Pacheco, and
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. Our code is available at https://github.com/koeppl/phoni.