GeneBreak

GeneBreak identifies genes that are recurrently affected by chromosomal breakpoints associated with copy number aberrations (CNAs) in cancer genomes to detect non-random breakpoint-associated genes across tumor cohorts.

Key Features:

• Systematic Detection of Structural Aberrations: Performs genome-wide detection of CNA-associated chromosomal breaks to analyze structural chromosomal aberrations beyond numerical CNAs.
• Integration with Existing Data: Uses DNA copy number data from array-Comparative Genomic Hybridization (CGH) or low-pass whole genome sequencing (WGS) and leverages genomic break locations derived from segmentation algorithms.
• Tailored Annotation for Breakpoint-to-Gene Mapping: Maps breakpoint coordinates to genes using a specialized annotation approach to identify genes recurrently affected by breaks.
• Cohort-Based Statistical Analysis: Applies cohort-based statistics with corrections for covariates influencing the likelihood of a gene being a breakpoint gene.
• Multiple Testing Correction: Implements multiple testing correction methods to control false positives when identifying significant recurrent breakpoint genes.

Scientific Applications:

• Cancer genomics: Identifies genes non-randomly affected by chromosomal breakpoints to inform studies of somatic alterations, including numerical and structural chromosomal aberrations in tumor genomes.
• Driver gene discovery: Highlights potential oncogenes and tumor suppressor genes involved in tumorigenesis by detecting recurrent breakpoint-associated gene disruptions.

Methodology:

Collects genomic locations of CNA-associated breaks from segmentation algorithms applied to CNA profiles derived from array-CGH or low-pass WGS; maps breakpoints to genes via tailored annotation; applies cohort-based statistical analysis with covariate corrections followed by multiple testing correction to identify significant recurrent breakpoint genes.