GEPIA

GEPIA provides analysis of RNA sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project to quantify gene expression and support differential expression, correlation, survival and dimensionality-reduction analyses for cancer genomics research.

Key Features:

• Differential Expression Analysis: Performs differential expression analysis between sample groups using RNA sequencing data to identify genes with altered expression.
• Profiling Plotting: Generates expression profile visualizations across samples and datasets to represent gene expression patterns.
• Correlation Analysis: Computes pairwise gene expression correlations to assess relationships between genes.
• Patient Survival Analysis: Links gene expression levels with clinical survival data to support prognostic analyses.
• Similar Gene Detection: Identifies genes with similar expression patterns to reveal functionally related genes or candidate biomarkers.
• Dimensionality Reduction Analysis: Applies dimensionality reduction techniques to simplify high-dimensional expression data and reveal patterns.

Scientific Applications:

• Cancer Genomics: Facilitates analysis of tumor RNA-seq data from TCGA to study gene expression changes in cancer.
• Cross-dataset Expression Comparison: Enables comparison of gene expression across TCGA and GTEx datasets to examine expression differences among sample collections.
• Biomarker and Prognostic Studies: Supports biomarker discovery and prognostic investigations by combining expression profiling, similarity detection, and survival analysis.

Methodology:

Analyzes publicly available RNA sequencing data from TCGA and GTEx and implements differential expression analysis, expression profile plotting, correlation analysis, patient survival analysis, similar-gene detection, and dimensionality-reduction techniques.