Summary: Kmer-db is a new tool for estimating evolutionary relationship on the basis of k-mers extracted from genomes or sequencing reads. Thanks to an efficient data structure and parallel implementation, our software estimates distances between 40 715 pathogens in <7 min (on a modern workstation), 26 times faster than Mash, its main competitor. Availability and implementation: https://github.com/refresh-bio/kmer-db and http://sun.aei.polsl.pl/REFRESH/kmer-db. Supplementary information: Supplementary data are available at Bioinformatics online.

Summary: Presence of sequencing errors in data produced by next-generation sequencers affects quality of downstream analyzes. Accuracy of them can be improved by performing error correction of sequencing reads. We introduce a new correction algorithm capable of processing eukaryotic close to 500 Mbp-genome-size, high error-rated data using less than 4 GB of RAM in about 35 min on 16-core computer. Availability and Implementation: Program is freely available at http://sun.aei.polsl.pl/REFRESH/reckoner . Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

SUMMARY: Counting all k -mers in a given dataset is a standard procedure in many bioinformatics applications. We introduce KMC3, a significant improvement of the former KMC2 algorithm together with KMC tools for manipulating k -mer databases. Usefulness of the tools is shown on a few real problems. AVAILABILITY AND IMPLEMENTATION: Program is freely available at http://sun.aei.polsl.pl/REFRESH/kmc . CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.