DEGreport

DEGreport generates HTML reports summarizing differential expression analyses of count data from RNA-seq experiments by integrating outputs and methods from DESeq2 and edgeR to present ranked genes by fold change and variability.

Key Features:

• Integration with DESeq2 and edgeR: Incorporates methodologies and code elements referenced in the DESeq2 and edgeR vignettes to process differential expression results.
• HTML report generation: Produces HTML reports that compile differential expression results and associated metrics.
• Ranked gene metrics: Presents fold changes, mean expression, and variability for genes to support prioritization.
• Bioconductor interoperability: Operates within the Bioconductor ecosystem to enable compatibility with other Bioconductor packages and data structures.
• Count data support: Targets count-based gene expression data derived from RNA-seq experiments.

Scientific Applications:

• Differential expression discovery: Identifies genes with changes in expression between experimental conditions using DESeq2- and edgeR-derived metrics.
• Gene prioritization: Facilitates selection of genes for downstream validation by ranking on fold change, mean, and variability.
• Functional and regulatory investigation: Summarizes differential expression results to support studies of gene function, regulatory mechanisms, and molecular bases of disease.

Methodology:

Integrates code elements from DESeq2 and edgeR vignettes, calculates fold changes and assesses expression variability, and ranks genes by fold change, mean, and variability for inclusion in HTML reports.