mdgsa

mdgsa performs gene set analysis across multiple genomic dimensions, emphasizing microRNAs (miRNAs) to analyze multidimensional cancer genomics datasets such as those from TCGA and ICGC.

Key Features:

• Multidimensional Data Analysis: Analyzes gene expression (RNA and miRNA), DNA methylation, and DNA copy number variations within a unified gene set analysis framework.
• miRNA-centric Analysis: Places particular emphasis on microRNAs (miRNAs) in gene set analyses.
• Visualization Capabilities: Provides visualization methods including a Matrix Layout for structured sample and data views and a Combined Biological Network and Circular Layout to display interconnections between biological networks.
• Integration with R Environment: Implemented as part of the caOmicsV package in the R programming environment.
• High-throughput Consortium Data Handling: Operates on large multidimensional datasets generated by high-throughput initiatives such as TCGA and ICGC.

Scientific Applications:

• Cancer diagnosis: Supports integrative analysis to identify genomic alterations relevant to cancer diagnosis.
• Prognostic marker identification: Enables identification of genetic markers associated with disease prognosis.
• Targeted therapeutics: Facilitates exploration of gene expression patterns and genomic alterations to inform targeted therapeutic development.

Methodology:

Performs gene set analysis across gene expression (RNA and miRNA), DNA methylation, and copy number variation data; generates plot datasets from multiple genomic datasets based on specified gene and sample names; and implements visualization via Matrix and Combined Biological Network/Circular layouts within the caOmicsV R package.