kASA: Taxonomic Analysis of Metagenomic Data on a Notebook

The taxonomic analysis of sequencing data has become important in many areas of life sciences. However, currently available software tools for that purpose either consume large amounts of RAM or yield an insufficient quality of the results. Here we present kASA, a k-mer based software capable of identifying and profiling metagenomic sequences with high computational efficiency and a small user-definable memory footprint. We ensure high sensitivity and precision via k-mers on amino acid level with a dynamic length of multiple k's as well as custom algorithms and data structures that are optimised for external memory storage enable for the first time a full-scale metagenomics analysis without compromise on a standard notebook.