rgsepd

rgsepd performs transcriptome analysis of RNA-Seq count data using R and Bioconductor, applying DESeq2 for differential expression, GOSeq for gene set enrichment, and N-dimensional projection to quantify sample relationships.

Key Features:

• Differential Expression Analysis: Uses DESeq2 to identify genes that are differentially expressed between treatment groups from RNA-Seq count data.
• Gene Set Enrichment: Uses GOSeq to perform gene set enrichment analysis and identify enriched Gene Ontology terms or predefined gene sets.
• N-Dimensional Projection: Implements N-dimensional projection techniques to quantify and visualize how each sample relates to different treatment groups.
• R and Bioconductor Integration: Built in R and integrated with the Bioconductor ecosystem to interoperate with other Bioconductor packages.

Scientific Applications:

• Comparative gene expression analysis: Identification of genes differentially expressed across experimental conditions or treatments using RNA-Seq count data.
• Pathway and GO interpretation: Interpretation of differential expression results through enrichment of Gene Ontology terms or predefined gene sets via GOSeq.
• Multi-condition sample relationship analysis: Assessment of sample relationships, clustering, and treatment effects in multi-dimensional space using N-dimensional projection.

Methodology:

Performs differential expression analysis with DESeq2; conducts gene set enrichment analysis with GOSeq; applies N-dimensional projection methods to quantify and visualize sample relationships; implemented in R and integrated with Bioconductor.