Tax4Fun2

Tax4Fun2 predicts habitat-specific functional profiles and assesses functional gene redundancy in prokaryotic communities from 16S rRNA gene sequences.

Key Features:

• R package implementation: Implemented as an R package for computational analysis of 16S rRNA gene data.
• Functional profile prediction: Predicts functional profiles of microbial communities from 16S rRNA gene sequences.
• Correlation with metagenomes: Produces predicted functional profiles that show high correlation with metagenomic-derived functional profiles from the same samples.
• Habitat-specific reference integration: Incorporates user-defined habitat-specific genomic information to refine functional predictions.
• Functional gene redundancy analysis: Quantifies functional gene redundancies within prokaryotic communities to assess potential community resilience.
• Comparative performance: Demonstrates improved accuracy compared to PICRUSt and the original Tax4Fun in environments with underrepresented genomic data.

Scientific Applications:

• Microbial ecology: Infers functional potential of microbial communities to support ecological interaction studies.
• Ecosystem function and resilience: Assesses functional contributions and redundancy relevant to ecosystem services and responses to environmental change.
• Soil microbiology: Applies functional inference to soil microbial community studies.
• Marine biology: Applies functional inference to marine microbial community studies.
• Environmental biotechnology: Supports evaluation of microbial functional potential in biotechnological and environmental management contexts.

Methodology:

Implemented in R, Tax4Fun2 uses 16S rRNA gene sequence data combined with user-provided habitat-specific genomic reference information to predict functional profiles, quantify functional gene redundancy, and compare predicted profiles to metagenomic-derived functional profiles.