strainberry

Strainberry performs automated strain separation in single-sample low-complexity metagenomes using long-read data to resolve strain-level genomes from microbial communities.

Key Features:

• Strain-resolved assembly: Produces strain-resolved assemblies with near-complete reference coverage and 99.9% base accuracy on mock communities.
• Genomic material recovery: Generates 20-118% additional genomic material on individual strain genomes compared to conventional metagenome assemblies on real datasets.
• Strain genome separation: Achieves complete separation of strain genomes to refine microbial diversity characterization in complex microbiomes.
• Long-read exclusive dependency: Relies uniquely on long-read sequencing data without requiring short-read input for strain separation.

Scientific Applications:

• Microbial community analysis: Enables resolution of multiple strains within the same species to distinguish their functional roles in microbiomes.
• Bacterial genome assembly from complex microbiomes: Supports accurate assembly of bacterial genomes for strain-level characterization.
• Mock community benchmarking: Validates performance using defined microbial communities with known reference genomes.
• Real microbiome dataset improvement: Enhances existing metagenome assemblies by recovering additional strain-specific genomic content.

Methodology:

Strainberry uses a metagenome assembly pipeline that performs strain separation using long-read data on single-sample low-complexity metagenomes.