MiGA

MiGA classifies unknown query genomic sequences against a comprehensive database of taxonomically classified genomes to enable genome-based taxonomic assignment and comparative analyses.

Key Features:

• Genomic Sequence Classification: Classifies complete or partial query genomic sequences against a database of taxonomically classified taxa, including cultivated and uncultivated genomes.
• Average Nucleotide and Amino Acid Identity (ANI/AAI): Uses genome-aggregate ANI and AAI metrics to assess genomic similarity and diversity at nucleotide and protein levels.
• Input Flexibility: Accepts raw reads and assemblies from isolate genomes, single-cell sequences, and metagenome-assembled genomes (MAGs).
• Clade Project Analysis: Analyzes hundreds of closely related genomes in Clade Projects to evaluate gene content diversity and calculate pangenome and core gene sets.
• Sequence preprocessing: Integrates sequence quality trimming and assembly to support downstream analyses.

Scientific Applications:

• Genome-based taxonomy: Supports taxonomic assignment of query genomes using ANI/AAI comparisons to classified reference genomes.
• Diversity and evolutionary analysis: Enables assessments of genomic diversity and evolutionary dynamics via ANI/AAI metrics and pangenome/core gene comparisons.
• Environmental and clinical genomics: Applies to environmental and clinical research for exploration of microbial biodiversity and adaptation mechanisms.
• Comparative clade genomics: Facilitates comparative analysis of closely related taxa through Clade Project pangenome and core gene evaluations.

Methodology:

Classification against a comprehensive genome database using genome-aggregate ANI and AAI metrics; calculation of pangenome and core gene sets for Clade Projects; and sequence quality trimming and assembly.