The rapid development of high-throughput sequencing technologies means that hundreds of
gigabytes of sequencing data can be produced in a single study. Many bioinformatics tools …

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 …

Post-Sanger sequencing methods produce tons of data, and there is a generalagreement
that the challenge to store and process them must be addressedwith data compression. In …

Motivation: Building the histogram of occurrences of every k-symbol long substring of
nucleotide data is a standard step in many bioinformatics applications, known under the …

Motivation: An accurate genome assembly from short read sequencing data is critical for
downstream analysis, for example allowing investigation of variants within a sequenced …

Motivation: Rapid advances in next-generation sequencing (NGS) technology have led to
exponential increase in the amount of genomic information. However, NGS reads contain far …

Background A basic task in bioinformatics is the counting of k-mers in genome sequences.
Existing k-mer counting tools are most often optimized for small k< 32 and suffer from …

Abstract de Bruijn graphs play an essential role in bioinformatics, yet they lack a universal
scalable representation. Here, we introduce simplitigs as a compact, efficient, and scalable …

K-mer abundance analysis is widely used for many purposes in nucleotide sequence
analysis, including data preprocessing for de novo assembly, repeat detection, and …

Motivation: Counting the frequencies of k-mers in read libraries is often a first step in the
analysis of high-throughput sequencing data. Infrequent k-mers are assumed to be a result …