CancerLivER

CancerLivER integrates and curates liver cancer transcriptomics and biomarker data to support gene expression analysis, biomarker identification, and pathway-level interpretation in liver cancer research.

Key Features:

• Curated gene expression datasets: Contains 115 curated gene expression datasets comprising 9,611 samples that were manually reviewed to remove artifacts.
• Standardized processing pipeline: Applies a standardized processing pipeline tailored to the specific experimental techniques used in each dataset.
• Comprehensive biomarker catalog: Includes 594 liver cancer biomarkers, comprising 315 gene biomarkers or signatures, 178 protein-based biomarkers, and 46 miRNA-based biomarkers.
• Integrated analysis and visualization: Includes analysis tools for visualization based on individual genes, Gene Ontology (GO), and pathways.
• Dataset matrix download: Provides a dataset matrix download feature to support external analyses aimed at identifying robust disease-specific signatures.

Scientific Applications:

• Biomarker discovery: Enable identification and prioritization of therapeutic targets and diagnostic markers using curated biomarkers and expression data.
• Signature identification and differential expression: Support discovery of disease-specific gene signatures and differential expression patterns across cohorts.
• Functional and pathway analysis: Facilitate Gene Ontology and pathway-based interpretation of gene expression changes.
• Cross-cohort meta-analysis: Enable cross-dataset/meta-analysis across 115 datasets and 9,611 samples to validate findings and assess reproducibility.

Methodology:

Manual curation to remove artifacts followed by application of a standardized, dataset-specific processing pipeline according to the techniques used for each dataset.