An Effective Parameter-free Comparison of NGS Short Reads for Phylogeny Reconstruction

Abstract

With the growth of the amount of genomic data generated from high-throughput sequencing, next-generation sequencing (NGS) has become the mainstream format for genome sequence data. NGS presents new challenges for many applications for genome sequence analysis. In sequence comparison applications, traditional multiple-sequence alignment approaches do not provide a solution for analyzing NGS data because of the short-read assembly and computational resource problems. Thus, alignment-free methods are more suitable for NGS data comparisons. Most of the alignment-free methods are based on the k-mer algorithm. However, the characteristics of NGS data make such k-mer-based methods suboptimal because the k parameter is a crucial factor in distance measurement and for the construction of phylogenetic trees. We propose an effective parameter-free comparison of NGS short reads, with the aim of eliminating the dependency on the k parameters. We compared the proposed method with existing methods, and the results show that the proposed method can measure accurate distances for the dataset without requiring any parameter.