Constrained enumeration of k-mers from a collection of references with metadata

Abstract

While recent developments in k-mers indexing methods have opened up many new possibilities, they still have limitations in handling certain types of queries, such as identifying k-mers present in one dataset but absent in another. In this article, we present a framework for efficiently enumerating all k-mers within a collection of references that satisfy constraints related to their metadata tags. Our method involves simplifying the query beforehand to reduce computation delays; the construction of the solution itself is carried out using CBL, a recent data structure specifically dedicated to the optimised computation of set operations on k-mer sets. We provide an implementation to our solution and we demonstrate its capabilities using real genomic data (microbial and RNA-seq), and show examples of use cases to identify k-mers of biological interest. FundingThis work is funded by a grant from the French ANR: Full-RNA ANR-22-CE45-0007. Igor Martayan is supported by a doctoral grant from ENS Rennes.