KAT

KAT performs reference-free quality control and analysis of whole genome shotgun (WGS) next-generation sequencing (NGS) data by examining k-mer frequencies and GC content to assess the quality, composition, and potential contamination of reads and de novo assemblies.

Key Features:

• Reference-free analysis: Operates without a reference genome to evaluate sequencing reads and assemblies from WGS NGS data.
• K-mer frequency analysis: Computes and examines k-mer frequencies and distributions to characterize sequence structure and coverage.
• GC-content analysis: Profiles GC composition of reads and assemblies to identify composition biases.
• Error, bias and contamination assessment: Evaluates levels of sequencing errors, biases, and contamination in input reads and resultant assemblies.
• Pairwise k-mer comparison: Performs pairwise comparisons of k-mers between input reads and assembled genomes to assess assembly composition and detect discrepancies.
• De novo assembly evaluation: Provides metrics on k-mer distribution and GC composition specifically applicable to de novo genome assemblies.

Scientific Applications:

• Read quality control: Assess quality, composition, and contamination of WGS NGS reads using k-mer and GC analyses.
• Assembly quality assessment: Evaluate de novo genome assemblies for completeness, representation, and composition via k-mer comparisons.
• Contamination and misassembly detection: Identify contamination or misassembly events by detecting k-mer discrepancies between reads and assemblies.
• Assembly optimization support: Inform optimization of assembly strategies and parameters by providing k-mer and GC composition metrics.

Methodology:

Computational methods explicitly include k-mer frequency counting and distribution analysis, GC-content profiling, and pairwise k-mer comparisons between reads and assemblies in a reference-free framework.