KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• De novo genome assembly from whole genome shotgun (WGS) sequencing data requires high-quality input with sufficient coverage.
• Assessing the quality and quantity of useful reads without a reference genome is a significant challenge in practice.
• Understanding WGS data characteristics and assembler utilization is crucial for improving genome assembly outcomes.

Purpose of the Study:

• To introduce the K-mer Analysis Toolkit (KAT), a software suite for reference-free quality control of WGS reads and de novo genome assemblies.
• To enable users to evaluate errors, biases, and contamination levels throughout the genome assembly pipeline.
• To demonstrate KAT's utility in gaining insights into genome assembly composition and quality.

Main Methods:

• Utilizes k-mer frequencies and GC composition for quality assessment.
• Performs pairwise comparison of k-mers between input reads and assembled genomes.
• Provides a multi-purpose software toolkit for comprehensive analysis.

Main Results:

• KAT facilitates reference-free quality control of WGS reads and de novo assemblies.
• The toolkit allows for the assessment of errors, bias, and contamination.
• Pairwise k-mer comparison offers valuable insights into assembly quality and composition.

Conclusions:

• KAT is a valuable tool for assessing the quality of WGS data and de novo genome assemblies.
• The software aids in identifying and mitigating issues during the assembly process.
• Reference-free analysis using k-mer frequencies enhances genome assembly quality and reliability.