MINTyper

MINTyper generates single nucleotide polymorphism (SNP) distance matrices from Illumina and Oxford Nanopore Technologies (ONT) sequencing reads to support SNP typing and detection of clonal outbreaks.

Key Features:

• Versatile Input Compatibility: Processes short reads from Illumina and long reads from Oxford Nanopore Technologies (ONT), including MinION data.
• Automated Workflow Pipeline: Automatically performs reference identification, alignment and trimming, and optional masking of methylation sites.
• SNP Distance Matrix Generation: Generates a SNP distance matrix from sequencing reads to enable clustering of sequenced isolates.
• Pairwise Distance Calculations: Calculates pairwise genetic distances between isolates to facilitate clustering and comparison.
• Adaptability to Read Quality: Supports methylation-aware base-called MinION reads (hac_m Q10) and fast base-called reads (fast Q8), can combine ONT reads with Illumina data, and adjusts the number of base pairs considered in distance calculations based on read quality.
• Consistent Clustering Across Read Qualities: Produces nearly identical clustering outcomes across varying ONT read qualities by tuning input parameters.

Scientific Applications:

• Clinical outbreak detection: Rapid identification of clonal clusters in clinical microbiology using SNP typing from sequencing reads.
• Epidemiological investigations: Clustering and confirmation of epidemiological relationships among isolates for transmission analysis.
• Genomic surveillance and infection control: Detection and investigation of outbreaks caused by genetically similar pathogen strains to inform infection control strategies.

Methodology:

From sequencing reads, MINTyper identifies suitable reference genomes, aligns reads to the reference and trims alignments, optionally masks methylation sites, generates SNP distance matrices and pairwise distance calculations, and adjusts parameters (including number of base pairs considered) to accommodate Illumina and ONT read types and qualities such as hac_m Q10 and fast Q8.