FROMP

FROMP maps enzyme annotations from metagenomic and metatranscriptomic datasets onto KEGG and custom metabolic pathways and computes pathway-level scores to profile and compare metabolic potential across samples.

Key Features:

• Pathway Mapping and Visualization: Maps enzyme annotations onto KEGG metabolic pathways and user-defined custom pathways and provides pathway-level visualizations of metabolic processes.
• Comparative Analysis Metrics: Calculates Pathway Completeness Scores, relative Activity Scores, and enzyme enrichment odds ratios to compare metabolic capabilities across samples.
• Score Matrices Generation: Produces score matrices for multiple meta-omics samples that are compatible with downstream statistical programs.
• Integration with Meta2Pro: Integrates with Meta2Pro, a PERL-based annotation organization pipeline, for annotation organization and downstream profiling.
• Implementation and Scalability: Implemented in Java and applied to large-scale metagenomic and metatranscriptomic datasets.

Scientific Applications:

• Environmental Microbiology: Profiling metabolic functions of environmental microbial communities using KEGG-based pathway mappings.
• Microbial Ecology: Comparing functional diversity and metabolic potential among communities and treatments.
• Systems Biology: Integrating pathway-level enzyme annotations and activity scores for systems-level metabolic analysis.
• Comparative Genomics and High-throughput Analysis: Generating matrix-based outputs for comparative analyses of meta-omic samples and experimental conditions.

Methodology:

Automated organization and annotation of metagenomic and metatranscriptomic data; mapping enzyme annotations to KEGG or custom pathways using the KEGG database; computation of Pathway Completeness Scores, relative Activity Scores, and enzyme enrichment odds ratios; generation of score matrices; integration with the PERL-based Meta2Pro pipeline; implemented in Java.