Efficient minimizer orders for large values of <i>k</i> using minimum decycling sets

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 sub-sequence 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. Unfortunately, generating compact universal k -mer hitting sets is currently infeasible for k &gt; 13, and thus 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 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 up to 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.