Coral

Coral enables creation, iterative refinement, and visual analysis of patient cohorts to identify and characterize subgroups using metadata and genomic markers (biomarkers) in computational cancer research.

Key Features:

• Cohort creation and refinement: Supports dynamic creation and iterative refinement of cohorts based on metadata attributes and genomic markers.
• Patient stratification by metadata and genomic markers: Stratifies patients using clinical metadata and genomic markers indicative of treatment response.
• Cohort comparison and item-level inspection: Provides detailed comparison, characterization, and inspection at the level of individual items.
• Visual evolution tracking: Visualizes changes in cohort composition across parameter adjustments to track cohort evolution.
• Prevalence information: Delivers prevalence data for cohort characteristics within larger datasets.
• Session management for reproducibility: Stores and shares analysis sessions to enable reproduction of findings.
• Extensive pre-loaded datasets: Includes over 128,000 samples from AACR Project GENIE, The Cancer Genome Atlas (TCGA), and the Cell Line Encyclopedia.

Scientific Applications:

• Patient subgroup identification and stratification: Identifies and characterizes clinically or molecularly distinct patient subgroups for computational cancer research.
• Biomarker discovery and treatment-response analysis: Associates genomic markers and biomarkers with response patterns to inform therapeutic hypotheses.
• Prevalence and cohort evolution analysis: Quantifies prevalence and tracks cohort evolution to support epidemiological and longitudinal interpretation.
• Genomic–clinical correlation for personalized therapy: Characterizes genomic and clinical correlates to support studies of personalized treatment strategies.

Methodology:

Cohorts are formed and iteratively refined from input parameters on patient metadata and genomic markers; cohort composition and prevalence are visualized to track evolution across parameter changes; analysis sessions can be stored and shared to reproduce results.