MIntO

MIntO integrates metagenomic and metatranscriptomic datasets to compute gene expression profiles and characterize functional dynamics of microbial communities across conditions and time.

Key Features:

• Integration of Metagenomic and Metatranscriptomic Data: Integrates metagenomic and metatranscriptomic datasets to compute gene expression profiles while accounting for community turnover and gene expression variation across samples.
• Modular Design and Operational Modes: Modular architecture supports three operational modes tailored to different input data and experimental designs.
• De novo Assembly into MAGs: Includes a de novo assembly mode to assemble metagenomes into metagenome-assembled genomes (MAGs) for genome-resolved functional analysis.
• Scalability: Designed to handle large-scale datasets across diverse biomes without requiring cultivation of microbial samples.
• Standardized Workflow and Pre‑processing: Implements standardized pre-processing and analysis steps to promote consistency and comparability across studies.

Scientific Applications:

• Microbial Ecology Insights: Links genomic functions to retrieved genomes and gene expression patterns to provide biochemical insights into microbial community roles and dynamics.
• Human Health and Environmental Studies: Enables functional characterization of microbial communities to support studies of microbiome contributions to human health and environmental processes.

Methodology:

Performs integration of metagenomic and metatranscriptomic datasets, computation of gene expression profiles with accounting for community turnover, optional de novo assembly into metagenome-assembled genomes (MAGs), and standardized pre-processing and analysis within a modular workflow.