Metalog

Metalog curates and harmonises contextual metadata for global metagenomic sequencing samples, enabling cross-study comparisons and meta-analyses through consistent annotation and links to genome-based analyses.

Key Features:

• Manually Curated Metadata: The database contains 73,082 human samples (including 58,506 gut microbiome samples), 10,703 animal samples, 5,146 ocean water samples, and 21,802 samples from other environmental habitats such as soil, sediment, or fresh water.
• Habitat-Specific Core Feature Annotation: Samples are consistently annotated for habitat-specific core features including demographics, disease status and medication for humans, host species and captivity status for animals, and filter sizes and salinity for marine samples.
• Original Metadata Preservation: All original metadata is provided in tabular form, simplifying focused studies such as investigations into nutrient concentrations.
• Pre-computed Taxonomic Profiles: Pre-computed taxonomic profiles facilitate rapid data exploration.
• Integration with SPIRE Database: Links to the SPIRE database enable genome-based analyses.

Scientific Applications:

• Cross-Study Comparisons: The consistent annotation of metadata facilitates comparisons across multiple metagenomic studies.
• Meta-Analyses: The harmonised metadata enables meta-analyses of global metagenomic datasets.
• Human Microbiome Research: The extensive collection of human gut microbiome samples supports research into host-microbe interactions, demographics, disease status and medication effects.
• Animal Microbiome Research: The curated animal samples support studies of host species effects and captivity status on microbial communities.
• Environmental Metagenomics: Ocean, soil, sediment and fresh water samples enable research into environmental microbial ecology, including studies of nutrient concentrations, filter sizes and salinity effects.
• Rapid Data Exploration: Pre-computed taxonomic profiles allow researchers to quickly assess taxonomic composition across samples.
• Genome-Based Analyses: Integration with SPIRE enables downstream genome-resolved analyses of metagenomic data.

Methodology:

Metadata was manually curated from primary publications and public databases, with samples consistently annotated for habitat-specific core features; pre-computed taxonomic profiles were generated to facilitate data exploration.