CORE

CORE identifies genomic regions with recurrent DNA copy number alterations across multiple samples to characterize recurrent events in cancer genomes.

Key Features:

• Recurrent Copy Number Alteration Detection: Identifies genomic intervals that exhibit recurrent DNA copy number alterations across multiple cancer samples.
• Genomic Interval Analysis: Analyzes collections of genomic intervals to detect regions with statistically recurrent patterns of copy number change.
• Cancer-Type Pattern Identification: Detects recurrence patterns characteristic of specific cancer types from aggregated genomic datasets.

Scientific Applications:

• Cancer Genomics Analysis: Identifies recurrent DNA copy number alterations associated with tumor development and progression.
• Genomic Aberration Discovery: Detects genomic regions frequently altered across cancer cohorts.
• Candidate Cancer Gene Identification: Supports identification of genomic loci potentially associated with oncogenes or tumor suppressor genes.

Methodology:

CORE analyzes collections of genomic intervals representing DNA copy number alterations across samples and identifies regions exhibiting recurrent events indicative of shared genomic aberrations.