Abstract
Development of cancer is driven by somatic alterations, including numerical and structural chromosomal aberrations. Currently, several computational methods are available and are widely applied to detect numerical copy number aberrations (CNAs) of chromosomal segments in tumor genomes. However, there is lack of computational methods that systematically detect structural chromosomal aberrations by virtue of the genomic location of CNA-associated chromosomal breaks and identify genes that appear non-randomly affected by chromosomal breakpoints across (large) series of tumor samples. 'GeneBreak' is developed to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach, which can be applied to DNA copy number data obtained by array-Comparative Genomic Hybridization (CGH) or by (low-pass) whole genome sequencing (WGS). First, 'GeneBreak' collects the genomic locations of chromosomal CNA-associated breaks that were previously pinpointed by the segmentation algorithm that was applied to obtain CNA profiles. Next, a tailored annotation approach for breakpoint-to-gene mapping is implemented. Finally, dedicated cohort-based statistics is incorporated with correction for covariates that influence the probability to be a breakpoint gene. In addition, multiple testing correction is integrated to reveal recurrent breakpoint events. This easy-to-use algorithm, 'GeneBreak', is implemented in R ( www.cran.r-project.org) and is available from Bioconductor ( www.bioconductor.org/packages/release/bioc/html/GeneBreak.html).
Highlights
Tumor development is driven by irreversible somatic genomic aberrations such as single nucleotide variants (SNVs) and chromosomal aberrations including numerical as well as structural changes[1,2]
R EV IS E D Amendments from Version 1. In this version we provide a much more extensive description of the underlying statistics for the detection of recurrent breakpoint events on genomic location- and gene-level
The actual locations of chromosomal copy number aberrations (CNAs)-associated breakpoints, which are the points of copy number level shift in somatic CNA profiles, indicate underlying chromosomal breaks and thereby genomic locations affected by somatic structural aberrations[5,6,7,8,9,10,11,12]
Summary
Any reports and responses or comments on the article can be found at the end of the article. Recurrent breakpoint genes, molecular characterization, cancer genome, copy number aberration profile, computational method. This article is included in the RPackage gateway. This article is included in the Bioconductor gateway. In this version we provide a much more extensive description of the underlying statistics for the detection of recurrent breakpoint events on genomic location- and gene-level. See referee reports ‘GeneBreak’ takes DNA copy number data that are pre-processed by the R-package ‘CGHcall’[13] or ‘QDNAseq’[14], both based on the Circular Binary Segmentation algorithm[15], as input. It is recommended to provide discrete DNA copy number states (e.g. loss, neutral, gain) that can be used for breakpoint selection. Bioconductor vignette and manual describe commands and workflows in detail (See Supplementary material)
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