Efficient minimizer orders for large values of k using minimum decycling sets
- David Pellow1,
- Lianrong Pu1,
- Bariş Ekim2,
- Lior Kotlar3,
- Bonnie Berger2,4,
- Ron Shamir1 and
- Yaron Orenstein5,6
- 1Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv 6997801, Israel;
- 2Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA;
- 3Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel;
- 4Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA;
- 5Department of Computer Science, Bar-Ilan University, Ramat-Gan 5290002, Israel;
- 6The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel
Abstract
Minimizers are ubiquitously used in data structures and algorithms for efficient searching, mapping, and indexing of high-throughput DNA sequencing data. Minimizer schemes select a minimum k-mer in every L-long subsequence of the target sequence, where minimality is with respect to a predefined k-mer order. Commonly used minimizer orders select more k-mers than necessary and therefore provide limited improvement in runtime and memory usage of downstream analysis tasks. The recently introduced universal k-mer hitting sets produce minimizer orders with fewer selected k-mers. Generating compact universal k-mer hitting sets is currently infeasible for k > 13, and thus, they cannot help in the many applications that require minimizer orders for larger k. Here, we close the gap of efficient minimizer orders for large values of k by introducing decycling-set-based minimizer orders: new minimizer orders based on minimum decycling sets. We show that in practice these new minimizer orders select a number of k-mers comparable to that of minimizer orders based on universal k-mer hitting sets and can also scale to a larger k. Furthermore, we developed a method that computes the minimizers in a sequence on the fly without keeping the k-mers of a decycling set in memory. This enables the use of these minimizer orders for any value of k. We expect the new orders to improve the runtime and memory usage of algorithms and data structures in high-throughput DNA sequencing analysis.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.277644.123.
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Freely available online through the Genome Research Open Access option.
- Received January 5, 2023.
- Accepted April 20, 2023.
This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
