KANALYZER: a method to identify variations of discriminative k-mers in genomic sequences

Abstract

Discriminative k-mers are unique genomic regions that characterize a given viral family, genus, species, or variant. Most existing algorithms for identifying discriminative k-mer sets are limited to returning raw sub-sequences. However, to explain the discriminative properties of a given k-mer for specific taxonomic groups of viruses, it is important to identify the variations (nucleotide sequences derived from an initial k-mer having undergone one or more nucleotide changes) of this k-mer that occur in other groups of viruses. These variations as well as their frequencies of occurrence, their genomic location and their potential influence on biological functions r epresent important insights to understand the classification process. In this article, we introduce KANALYZER, a novel algorithm to identify variations of discriminative k-mers and associated information according to viral taxonomy. The algorithm was assessed to identify k-mer variations in both simulated and real viral sequence sets. In these evaluations, KANALYZER correctly and quickly identified over 95% of the variations and associated information. KANALYZER algorithm is integrated directly into CASTOR-KRFE discriminative k-mers identification tool pipeline. The source code, detailed results and data to reproduce the experiments are available at https://github.com/bioinfoUQAM/CASTOR_KRFE.