DuctApe

DuctApe analyzes genomic sequences together with Phenotype Microarray (PM) data to correlate genes and KEGG-encoded metabolic pathways with microbial phenotypes.

Key Features:

• Integration of Genomic and Phenomic Data: Combines genomic information encoded as KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways with results from Phenotype Microarray (PM) experiments.
• OmniLog™ PM data analysis: Leverages OmniLog™ PM technology outputs to assess metabolic functionality of microorganisms.
• Gene–Phenotype Correlation: Links PM data with genes of interest and extracts gene-phenotype correlations using gene presence/absence patterns.
• Metabolic differences detection: Detects metabolic differences across experiments by comparing genomic sequences and PM measurements.
• Implementation: Implemented in Python.

Scientific Applications:

• Metabolic Pathway Reconstruction: Correlates genomic sequences with phenotypic data to support reconstruction of metabolic pathways via KEGG mappings.
• Biotechnological Manipulation: Identifies genes linked to specific phenotypes to inform manipulation of microbial metabolism for industrial applications.
• Microbial gene-phenotype analysis: Applied to four bacterial datasets to elucidate complex gene-phenotype relationships in microbial systems.

Methodology:

Analyzes genomic sequences alongside PM data to detect metabolic differences across experiments and correlates these findings with KEGG pathways and gene presence/absence patterns.