title: Informed and automated k-mer size selection for genome assembly.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  Our tool KmerGenie is freely available at: http://kmergenie.bx.psu.edu/.
authors.affiliation: Department of Computer Science and Engineering and Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA.
authors.forename: Rayan
authors.initials: R
authors.lastname: Chikhi
authors.forename: Paul
authors.initials: P
authors.lastname: Medvedev
mesh_terms: D000465:Algorithms; D000818:Animals; D001331:Automation; D016678:Genome; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D007313:Insecta; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software; D013211:Staphylococcus aureus