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We present a computational method that combines genome-wide DNA methylation and copy number variation data in an integrated fashion with the aim of finding mechanistic associations between genome instability and local DNA methylation changes. The method is applied to Luminal A breast cancer early-stage tumour samples and focuses on methylation events occurring at frequently rearranged genome locations. Our method accommodates array and sequencing platforms for methylation and DNA copy number estimates. We find significant local methylation changes in tumours tend to occur in the viscinity of breakpoint rich regions, with 80% of the differentially methylated regions occurring within 2Mb from a breakpoint rich locus.