Bioinformatics · 2016 · 601 citations · 8 references
Life SciencesBioinformaticsBiologyGenome AssemblyGenomicsSequence AnalysisDe Novo Genome AssemblyDna SequencingGenome SequencingReference-guided AssemblySequence AssemblySequence Quality ControlAssembly Quality AssessmentCoverageDe Novo AssemblyGc Content VariationK-mer Frequency AnalysisPairwise ComparisonRead Quality AssessmentRead Quality Control
Motivation: De novo assembly of whole genome shotgun (WGS) next-generation sequencing (NGS) data benefits from high-quality input with high coverage. However, in practice, determining the quality and quantity of useful reads quickly and in a reference-free manner is not trivial. Gaining a better understanding of the WGS data, and how that data is utilized by assemblers, provides useful insights that can inform the assembly process and result in better assemblies. Results: We present the K-mer Analysis Toolkit (KAT): a multi-purpose software toolkit for reference-free quality control (QC) of WGS reads and de novo genome assemblies, primarily via their k-mer frequencies and GC composition. KAT enables users to assess levels of errors, bias and contamination at various stages of the assembly process. In this paper we highlight KAT's ability to provide valuable insights into assembly composition and quality of genome assemblies through pairwise comparison of k-mers present in both input reads and the assemblies. Availability and Implementation: KAT is available under the GPLv3 license at: https://github.com/TGAC/KAT . Contact: bernardo.clavijo@earlham.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.
8
Genomic DNA k-mer spectra: models and modalities
Benny Chor, D. Horn, Nick Goldman et al. · Genome biology · 2009 · 260 citations · Full text
HTQC: a fast quality control toolkit for Illumina sequencing data
Xi Yang, Di Liu, Fei Liu et al. · BMC Bioinformatics · 2013 · 209 citations · Full text