title: KAnalyze: a fast versatile pipelined k-mer toolkit.
abstract: BACKGROUND
  Converting nucleotide sequences into short overlapping fragments of uniform length, k-mers, is a common step in many bioinformatics applications. While existing software packages count k-mers, few are optimized for speed, offer an application programming interface (API), a graphical interface or contain features that make it extensible and maintainable. We designed KAnalyze to compete with the fastest k-mer counters, to produce reliable output and to support future development efforts through well-architected, documented and testable code. Currently, KAnalyze can output k-mer counts in a sorted tab-delimited file or stream k-mers as they are read. KAnalyze can process large datasets with 2 GB of memory. This project is implemented in Java 7, and the command line interface (CLI) is designed to integrate into pipelines written in any language.
  
  
  RESULTS
  As a k-mer counter, KAnalyze outperforms Jellyfish, DSK and a pipeline built on Perl and Linux utilities. Through extensive unit and system testing, we have verified that KAnalyze produces the correct k-mer counts over multiple datasets and k-mer sizes.
  
  
  METHODS
  KAnalyze is available on SourceForge: https://sourceforge.net/projects/kanalyze/.
authors.affiliation: School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: Audano
authors.affiliation: School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.
authors.forename: Fredrik
authors.initials: F
authors.lastname: Vannberg
mesh_terms: D000465:Algorithms; D002878:Chromosomes, Human, Pair 1 / Q000737:chemistry; D006801:Humans; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software