BIS-SNP: COMBINED CYTOSINE METHYLATION AND SNP CALLING FOR BISULFITE SEQUENCE DATA

DNA methylation across the genome is an important readout of cancer progression, and can be measured using bisulfite treatment of DNA followed by hi-throughput sequencing or array analysis. We wrote algorithms and a workflow for analysis of bisulfite sequencing data while accounting for common genetic variants (which can alter the measured methylation levels. We encapsulated in a program titled Bis-SNP. We demonstrate improvement over existing methods and show 96% sensitivity at 30x genome coverage.

Abstract

Bisulfite treatment of DNA followed by high-throughput sequencing (Bisulfite-seq) is an important method for studying DNA methylation and epigenetic gene regulation, yet current software tools do not adequately address single nucleotide polymorphisms (SNPs). Identifying SNPs is important for accurate quantification of methylation levels and for identification of allele-specific epigenetic events such as imprinting. We have developed a model-based bisulfite SNP caller, Bis-SNP, that results in substantially better SNP calls than existing methods, thereby improving methylation estimates. At an average 30× genomic coverage, Bis-SNP correctly identified 96% of SNPs using the default high-stringency settings. The open-source package is available at http://epigenome.usc.edu/publicationdata/bissnp2011.

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RELEVANCE TO OC

This tool has been central to our efforts to analyze the changes in methylation levels genome-wide associated with ovarian cancer tumors.

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