UALCAN

UALCAN enables analysis of TCGA level 3 RNA-seq and associated clinical data to quantify gene expression differences, identify dysregulated genes, and assess associations with clinicopathologic features and patient survival across multiple cancer types.

Key Features:

• Data Source: Uses TCGA level 3 RNA-seq data and clinical information from 31 distinct cancer types.
• Gene Expression Analysis: Compares relative expression of specific genes between tumor and normal samples and within tumor sub-groups defined by cancer stage, tumor grade, race, body weight, and other clinicopathologic features.
• Survival Analysis: Evaluates associations between gene expression levels, clinicopathologic features, and patient survival to identify potential prognostic biomarkers.
• Gene Regulation Identification: Identifies top over-expressed and under-expressed genes in individual cancer types to pinpoint up-regulated and down-regulated candidate biomarkers or therapeutic targets.

Scientific Applications:

• In silico gene validation: Enables validation of target genes using TCGA RNA-seq and clinical data.
• Tumor sub-group biomarker discovery: Supports identification of candidate biomarkers specific to tumor sub-groups defined by stage, grade, race, body weight, and other clinicopathologic variables.
• Clinical association studies: Facilitates analysis of correlations between gene expression and patient survival or other clinical outcomes to study tumoral heterogeneity and potential therapeutic or diagnostic targets.

Methodology:

Performs analyses using TCGA level 3 RNA-seq and clinical datasets to assess gene expression differences between tumor and normal samples, analyze expression across tumor sub-groups, identify top over- and under-expressed genes, and evaluate associations with clinicopathologic features and patient survival.