CanDI

CanDI integrates heterogeneous cancer-related datasets by retrieving and indexing public and user-provided data to enable synthesis of multi-source genomic and functional information for hypothesis generation and therapeutic target identification.

Key Features:

• Retrieval and indexing framework: Systematic retrieval and indexing of publicly available datasets to support consolidated querying and analysis.
• User dataset integration: Incorporation of user-specific or bespoke datasets alongside public resources for customized analyses.
• Continuous data updates: Ongoing incorporation of new data to maintain the currency of integrated datasets.
• Hypothesis generation: Integrated analysis facilitates identification of synthetic lethal gene pairs, genes associated with sex disparity in cancer, and potential immunotherapy targets.

Scientific Applications:

• Large-scale cancer data integration: Consolidation of multi-source genomic and functional datasets for comprehensive analysis of cancer biology.
• Discovery of genetic interactions: Identification of synthetic lethal relationships and genes linked to sex disparities in cancer.
• Immunotherapy target identification: Support for discovery of candidate immunotherapy targets through integrated multi-dataset analysis.
• Therapeutic target prioritization: Facilitation of prioritizing candidate targets and generating testable hypotheses for experimental validation.

Methodology:

Systematic retrieval and indexing of data from public sources and integration of user-specific datasets to enable cohesive analysis of data from disparate origins.