Human Microbiome Dataset (Archaea, Viruses, Fungi and Bacteria)
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Description: This dataset was generated using CAMISIM (Community AMplification and SIMulation) to model a complex human microbiome community across 50 simulated patients. It includes sequencing data representing four major microbial groups: archaea, viruses, fungi, and bacteria. The dataset incorporates multiple closely related strains and species, reflecting the natural diversity and strain-level complexity observed in human-associated microbiomes. This design enables rigorous benchmarking of metagenomic workflows, particularly in scenarios where distinguishing between near-identical taxa is critical. Key Features: Synthetic metagenomic reads generated with CAMISIM 50 patient-specific microbiome communities Inclusion of rare taxa (fungi, archaea and viruses) alongside dominant bacterial populations Multiple closely related strains and species for strain-level benchmarking Dataset focuses on raw simulated reads; metadata files may be provided upon request (email: jagriti@mahanim.in) Potential Use Cases: Benchmarking of bioinformatics pipelines under realistic strain-level complexity Comparative evaluation of sequencing workflows Training datasets for machine learning models in microbiome analysis Educational resource for computational biology and metagenomics courses Format & Availability: FASTQ files of simulated reads (both forward and reverse FASTQ files have been uploaded for all 50 patients) Patient-level community design embedded in simulation Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)—users must credit the contributors when reusing or adapting this dataset
