RandomReadsMG: Rapid, realistic metagenome simulation at terabase scale for benchmarking and experimental design.

RandomReadsMG rapidly generates terabase-scale, realistic metagenomic datasets with customizable features, enabling efficient benchmarking and experimental planning.

• Why it matters: Accurate synthetic metagenomes are crucial for testing bioinformatics tools and designing experiments, but existing methods often lack speed or realism at large scales.
• What they did: The tool creates communities of up to 50,000 genomes with user-defined abundance, sequencing errors, and artifacts, supporting Illumina, ONT, and PacBio profiles, all within a single command.
• The result: It produces large datasets in under 6 hours with controlled memory use, facilitating reliable benchmarking, biosurveillance, and large-scale synthetic data generation for metagenomics research.