2018/08/29 by Philip T. L. C. Clausen, Frank M. Aarestrup, Ole Lund · 1 voice · 14 citations
Biochemistry, Genetics and Molecular Biology · #Antibiotic Resistance in Bacteria #Bacterial Identification and Susceptibility Testing #Genomics and Phylogenetic Studies
paper · pdf · doi:10.1186/s12859-018-2336-6
openalex publication_date 2018/08/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
BACKGROUND: As the cost of sequencing has declined, clinical diagnostics based on next generation sequencing (NGS) have become reality. Diagnostics based on sequencing will require rapid and precise mapping against redundant databases because some of the most important determinants, such as antimicrobial resistance and core genome multilocus sequence typing (MLST) alleles, are highly similar to one another. In order to facilitate this, a novel mapping method, KMA (k-mer alignment), was designed. KMA is able to map raw reads directly against redundant databases, it also scales well for large redundant databases. KMA uses k-mer seeding to speed up mapping and the Needleman-Wunsch algorithm to accurately align extensions from k-mer seeds. Multi-mapping reads are resolved using a novel sorting scheme (ConClave scheme), ensuring an accurate selection of templates. RESULTS: The functionality of KMA was compared with SRST2, MGmapper, BWA-MEM, Bowtie2, Minimap2 and Salmon, using both simulated data and a dataset of Escherichia coli mapped against resistance genes and core genome MLST alleles. KMA outperforms current methods with respect to both accuracy and speed, while using a comparable amount of memory. CONCLUSION: With KMA, it was possible map raw reads directly against redundant databases with high accuracy, speed and memory efficiency.