OSskcm

OSskcm performs survival analysis for cutaneous melanoma by integrating gene expression and clinical data to evaluate prognostic biomarkers.

Key Features:

• Data Integration: Integrates gene expression data with clinical information from 1085 samples sourced from TCGA and GEO databases.
• Implementation: Implemented with server-side JavaScript on a Windows Tomcat server and uses an SQL Server database to store and manage integrated data.
• Survival Analysis Tools: Generates Kaplan-Meier (KM) survival plots including log-rank P values and Hazard Ratios (HR) with 95% confidence intervals (CI) derived from univariate Cox regression.
• Subgroup Analysis: Performs prognostic analyses stratified by clinical characteristics including race, stage, gender, age, and type of therapy within melanoma patient subsets.

Scientific Applications:

• Prognostic biomarker assessment: Evaluates and validates candidate prognostic genes for cutaneous melanoma using integrated expression and clinical data.
• High-dimensional expression analysis: Facilitates analysis of large-scale gene expression profiles to identify potential prognostic genes in melanoma cohorts.

Methodology:

Collects and integrates gene expression and clinical datasets from TCGA and GEO (1085 samples) and applies univariate Cox regression to evaluate gene-level survival associations, producing Kaplan-Meier plots together with log-rank P values and HRs (95% CI).