bcgsc.ca_UCEC_IlluminaHiSeq_miRNASeq.whitelist_tumor
Created By Kyle Ellrott kellrott
Identification of copy number variants. To characterize somatic copy number alterations in the tumor genome, we applied a new algorithm called BIC-seq (Xi etal 2011) to low-coverage whole-genome sequencing data. First, we counted the reads (uniquely aligned to the reference genome with at least 46bp out of 50bp aligned) in fixed-size, non-overlapping windows along the genome. Given these bins with read counts for tumor and matched normal genomes, BIC-seq attempts to iteratively combine neighboring bins with similar copy numbers. Whether the two neighboring bins should be merged is based on Bayesian Information Criteria (BIC), a statistical criterion measuring both fitness and complexity of a statistical model. Segmentation stops when no merging of windows improves BIC, and the boundaries of the windows are reported as a final set of copy number breakpoints. Segments with copy ratio difference smaller than 0.1 (log2 scale) between tumor and normal genomes were merged in the post-processing step to avoid excessive refinement of altered regions with high read counts. Structural Variation Discovery with BreakDancer. Structural Variation detection is performed with the program BreakDancer on a .bam file constructed from HiSeq sequencing of each tumor pair (Chen etal 2009). The first step requires a configuration file of each bam file for each tumor pair with the bam2cfg.pl perl module of the program. After the configuration file, the perl module BreakDancerMax.pl is run on the configuration file in order to call structural variants in the tumor and control files. Each tumor structural variant file is filtered with its matched normal and all possible somatic variants are filtered with a metanormal to remove any false positives. Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, McGrath SD, Wendl MC, Zhang Q, Locke DP, et al: (2009) BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods 6:677-681. Xi R, Hadjipanayis AG, Luquette LJ, Kim TM, Lee E, Zhang J, Johnson MD, Muzny DM, Wheeler DA, Gibbs RA, et al: (2011) Copy number variation detection in whole-genome sequencing data using the Bayesian information criterion. Proc Natl Acad Sci USA 108: 1128-1136.
acronym: COAD
disease: cancer
species: Homo sapiens
platform: IlluminaHiSeq_DNASeqC
lastUpdate: 2012-07-17
tissueType: colon