Abstract
BackgroundSingle nucleotide polymorphisms (SNPs) are the most common genetic variations in the human genome and are useful as genomic markers. Oligonucleotide SNP microarrays have been developed for high-throughput genotyping of up to 900,000 human SNPs and have been used widely in linkage and cancer genomics studies. We have previously used Hidden Markov Models (HMM) to analyze SNP array data for inferring copy numbers and loss-of-heterozygosity (LOH) from paired normal and tumor samples and unpaired tumor samples.ResultsWe proposed and implemented major copy proportion (MCP) analysis of oligonucleotide SNP array data. A HMM was constructed to infer unobserved MCP states from observed allele-specific signals through emission and transition distributions. We used 10 K, 100 K and 250 K SNP array datasets to compare MCP analysis with LOH and copy number analysis, and showed that MCP performs better than LOH analysis for allelic-imbalanced chromosome regions and normal contaminated samples. The major and minor copy alleles can also be inferred from allelic-imbalanced regions by MCP analysis.ConclusionMCP extends tumor LOH analysis to allelic imbalance analysis and supplies complementary information to total copy numbers. MCP analysis of mixing normal and tumor samples suggests the utility of MCP analysis of normal-contaminated tumor samples. The described analysis and visualization methods are readily available in the user-friendly dChip software.
Highlights
Single nucleotide polymorphisms (SNPs) are the most common genetic variations in the human genome and are useful as genomic markers
Definition of major copy proportion The major copy proportion (MCP) of a SNP is defined as C2/(C1 + C2), where C1 and C2 are the parental copy numbers at this SNP in a sample and C1 ≤ C2
For a heterozygous SNP in a sample, raw allele A proportion (RAP) should vary by a certain noise level around the unobserved MCP or 1 – MCP; for a homozygous SNP, RAP is close to 1 for genotype AA and close to 0 for genotype BB, since one of RA and RB is close to 0
Summary
Single nucleotide polymorphisms (SNPs) are the most common genetic variations in the human genome and are useful as genomic markers. Loss of the contribution of one parent in selected chromosome regions can happen due to hemizygous deletion or mitotic gene conversion (termed loss of heterozygosity or LOH). When such alterations affect tumor-suppressor genes (TSG) or oncogenes and confer growth advantage to cells, they will be selected in descendant cells and contribute to cancer for-. BMC Bioinformatics 2008, 9:204 http://www.biomedcentral.com/1471-2105/9/204 mation [1] Identifying such abnormal copy number and LOH regions in tumor samples may help to identify cancer-related genes and provide clues about cancer initiation or growth [2,3]
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