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Coral is a web-based tool for computational cancer analysis, enabling researchers to identify patient subgroups using metadata or genomic markers. It facilitates interactive cohort creation, comparison, and data visualization for reproducible research.

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Area of Science:

  • Computational biology
  • Cancer research
  • Bioinformatics

Background:

  • Identifying patient subgroups is crucial for cancer analysis.
  • Stratification and biomarker discovery aid in understanding treatment response.
  • Existing tools may lack interactive features for cohort refinement.

Purpose of the Study:

  • To introduce Coral, a web-based tool for cohort analysis in cancer research.
  • To support interactive creation, refinement, and comparison of patient cohorts.
  • To provide visualization and session management for reproducible findings.

Main Methods:

  • Development of a web-based platform named Coral.
  • Integration of data from large-scale cancer genomics projects (AACR GENIE, TCGA, Cell Line Encyclopedia).
  • Implementation of interactive cohort building, visualization, and session management features.

Main Results:

  • Coral enables users to interactively define and refine patient cohorts.
  • The tool visualizes cohort evolution and provides prevalence information.
  • Findings can be stored, shared, and reproduced using Coral's session management.

Conclusions:

  • Coral offers a comprehensive and interactive solution for cohort analysis in cancer research.
  • The tool supports data-driven discovery through visualization and reproducible session management.
  • Coral is pre-loaded with extensive cancer genomics data, facilitating immediate use.