R2

R2 performs gene expression analysis and visualization and applies Kaplan-Meier survival analysis to investigate associations between molecular measurements and clinical outcomes.

Key Features:

• Gene expression analysis: Performs analysis of gene expression data to quantify and compare transcript levels across samples.
• Visualization: Generates visualizations of gene expression data for comparative and exploratory analyses.
• Kaplan-Meier survival analysis: Implements the Kaplan-Meier method for survival analysis to associate molecular measurements with patient outcomes.
• Prognostic marker and therapeutic target identification: Enables identification of expression patterns linked to prognostic markers and potential therapeutic targets.

Scientific Applications:

• Diffuse large B-cell lymphoma (DLBCL) studies: Analysis of 14-3-3beta gene expression in DLBCL compared to non-neoplastic lymph nodes using archived wax blocks from 120 patients.
• Clinical correlation analyses: Correlation of gene expression with clinical parameters including extra-nodal status and serum lactate dehydrogenase (LDH) levels.
• Survival outcome association: Assessment of associations between low 14-3-3beta expression and inferior overall survival using Kaplan-Meier analysis.
• Cancer biomarker discovery: Identification of expression signatures associated with adverse patient survival for use as prognostic markers or therapeutic targets.

Methodology:

Computational methods explicitly include gene expression analysis and Kaplan-Meier survival analysis.