SCORE

SCORE integrates multiple differential expression analysis pipelines to generate consensus-based identification of differentially expressed genes from bacterial RNA-sequencing (RNA-Seq) data.

Key Features:

• Consensus-based integration: Employs a Snakemake-based framework to combine results from multiple established differential expression tools into a unified consensus.
• End-to-end bacterial RNA-Seq workflow: Covers read preprocessing, differential expression analysis, and overrepresentation analysis of significantly associated ontologies.
• Improved prediction accuracy: Synthesizes diverse analytical outputs to enhance reliability of differentially expressed gene detection in the absence of a single gold standard.
• Unified, human-readable outputs: Merges varying tool results into a single interpretable summary of consensus calls and associated analyses.

Scientific Applications:

• Bacterial transcriptome analysis: Identification of differentially expressed genes from bacterial RNA-Seq experiments.
• Functional enrichment and ontology analysis: Overrepresentation analysis to associate differential expression with biological processes and pathways using ontologies.
• Microbial genomics benchmarking: Supports comparative evaluation of differential expression methods and the development of consensus-based standards for RNA-Seq analysis.

Methodology:

SCORE integrates multiple differential expression tools within a Snakemake-based pipeline performing read preprocessing, differential expression analysis, consensus aggregation, and overrepresentation analysis of ontologies.