ReporterScore

ReporterScore performs generalized reporter score–based enrichment analysis of high-dimensional omics datasets (microbiome, transcriptome, metabolome) to detect pathway- and taxonomy-level signals across multi-group and longitudinal experimental designs.

Key Features:

• Increased Sensitivity: GRSA demonstrates increased sensitivity relative to traditional enrichment methods across benchmark datasets.
• Multi-Group and Longitudinal Data Compatibility: GRSA applies to multi-group and longitudinal experimental designs by operating on raw feature values rather than P-values.
• Integration with Pathway Databases: ReporterScore integrates with pathway databases to enable pathway-level enrichment analysis.
• Versatile Application Beyond Functional Enrichment: The method can leverage taxonomy databases to extend analyses beyond traditional functional enrichment.

Scientific Applications:

• Microbiome analysis: Detects pathway- and taxonomy-level changes in microbiome datasets, including longitudinal studies.
• Transcriptomics: Interprets pathway-level signals in transcriptome data across multi-group comparisons.
• Metabolomics: Identifies enriched metabolic pathways in metabolome datasets and supports complex experimental designs.

Methodology:

ReporterScore extends reporter score-based analysis (RSA) by implementing a Generalized Reporter Score-based Analysis (GRSA) that operates on raw feature values instead of P-values to accommodate multi-group and longitudinal designs.