A K-Mer Based Sequence Similarity for Pangenomic Analyses

In this work we propose an approach to improve the performance of a current methodology, computing k-mer based sequence similarity via Jaccard index, for pangenomic analyses. Recent studies have shown a good performance of such a measure for retrieving homology among genetic sequences belonging to a group of genomes. Our improvement is obtained by exploiting a suitable k-mer representation, which enables a fast and memory-cheap computation of sequence similarity. Experimental results on genomes of living organisms of different species give an evidence that a state of the art methodology is here improved, in terms of running time and memory requirements.