Cancers are fundamentally caused by genomic changes in the cancer cells that lead to their uncontrolled growth (Balmain et al., 2003; Stratton et al., 2009). Understanding these changes, which include DNA copy number alterations, is an intense focus of current research into the causes of, and potential therapies for, every type of cancer. Major research projects, such as the Cancer Genome Atlas (TCGA) project (The Cancer Genome Atlas Research Network, 2008), aim to comprehensively catalog all genomic changes in cancer. This chapter discusses the problem of interpreting copy number data, specifically in the context of cancer research.
To measure copy number, whole-genome genotyping array assays hybridize sample DNA to oligonucleotides deposited on the array. Modern designs use synthetic oligonucleotides to measure copy number at frequent intervals along the genome, especially in regions of known copy number variation. Modern arrays also include many probes that target both alleles of a large number of common single-nucleotide polymorphisms (SNPs). These platforms are therefore widely used in genotyping studies. Array-based assays available for measuring genome-wide copy number include arrays from Illumina, Sentrix, Agilent, and Affymetrix. Data from next-generation sequencing of DNA can also be used to detect copy number alterations and is rapidly becoming cost competitive with array-based platforms.
Molecular inversion probe (MIP) arrays (Wang et al., 2007, 2009; Ji and Welch, 2009) are another platform that can be used for large-scale copy number analysis and genotyping. MIP technology uses less DNA, can handle lower quality DNA, has a greater dynamic range, has higher quality markers, and better separates allelic information than other array-based approaches.