Sign in
BioinformaticsbioRxiv
Preprint

Matchtigs: minimum plain text representation of kmer sets

Sebastian SchmidtiD, Shahbaz KhaniD, Jarno AlankoiD, Giulio Ermanno PibiriiD, Alexandru Ioan TomescuiD

Abstract

We propose a polynomial algorithm computing a minimum plain-text representation of kmer sets, as well as an efficient near-minimum greedy heuristic. When compressing read sets of large model organisms or bacterial pangenomes, with only a minor runtime increase, we shrink the representation by up to 60% over unitigs and 27% over previous work. Additionally, the number of strings is decreased by up to 97% over unitigs and 91% over previous work. Finally, a small representation has advantages in downstream applications, as it speeds up SSHash-Lite queries by up to 4.26x over unitigs and 2.10x over previous work. Availabilitymatchtigs: https://github.com/algbio/matchtigs SSHash-Lite: https://github.com/jermp/sshash-lite

PDFDOICode

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISRahman '20Diseth '26Rouzé '25Schmidt '23Sladký '23Pibiri '26
76% semantic matchBioinformatics
Amatur Rahman, Paul Medevedev·Journal of Computational Biology·Dec 8, 2020· 41 citations