Informed and automated k-mer size selection for genome assembly

Bioinformatics. 2014 Jan 1;30(1):31-7. doi: 10.1093/bioinformatics/btt310. Epub 2013 Jun 3.


Motivation: Genome assembly tools based on the de Bruijn graph framework rely on a parameter k, which represents a trade-off between several competing effects that are difficult to quantify. There is currently a lack of tools that would automatically estimate the best k to use and/or quickly generate histograms of k-mer abundances that would allow the user to make an informed decision.

Results: We develop a fast and accurate sampling method that constructs approximate abundance histograms with several orders of magnitude performance improvement over traditional methods. We then present a fast heuristic that uses the generated abundance histograms for putative k values to estimate the best possible value of k. We test the effectiveness of our tool using diverse sequencing datasets and find that its choice of k leads to some of the best assemblies.

Availability: Our tool KmerGenie is freely available at:

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Automation
  • Genome*
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Insecta
  • Sequence Analysis, DNA / methods
  • Software
  • Staphylococcus aureus