BioinformaticsBioinformaticsPeer-reviewed journal article
KAT: A K-mer Analysis Toolkit to quality control NGS datasets and genome assemblies
Daniel MaplesoniD, Gonzalo Garcia AccinelliiD, George KettleboroughiD, Jonathan WrightiD, Bernardo ClavijoiD
Abstract
MotivationDe novo assembly of whole genome shotgun (WGS) next-generation sequencing (NGS) data bene[fi]ts 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 utilised by assemblers, provides useful insights that can inform the assembly process and result in better assemblies.\n\nResultsWe 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 KATs 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.\n\nAvailabilityKAT is available under the GPLv3 license at: https://github.com/TGAC/KAT.\n\nContactbernardo.clavijo@earlham.ac.uk\n\nSupplementary InformationSupplementary Information (SI) is available at Bioinformatics online. In addition, the software documentation is available online at: http://kat.readthedocs.io/en/latest/.
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
- Citations
- 541
- FWCI
- 11.43
- Field percentile
- top 1%
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