Dataset Information

PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays.

ABSTRACT:

Motivation

Normalization is critical in DNA copy number analysis. We propose a new method to correctly identify two-copy probes from the genome to obtain representative references for normalization in single nucleotide polymorphism arrays. The method is based on a two-state Hidden Markov Model. Unlike most currently available methods in the literature, the proposed method does not need to assume that the percentage of two-copy state probes is dominant in the genome, as long as there do exist two-copy probes.

Results

The real data analysis and simulation study show that the proposed algorithm is successful in that (i) it performs as well as the current methods (e.g. CGHnormaliter and popLowess) for samples with dominant two-copy states and outperforms these methods for samples with less dominant two-copy states; (ii) it can identify the copy-neutral loss of heterozygosity; and (iii) it is efficient in terms of the computational time used.

Availability

R scripts are available at http://publichealth.lsuhsc.edu/PAIR.html.

SUBMITTER: Yang S

PROVIDER: S-EPMC3562063 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Publications

PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays.

Yang Shengping S Pounds Stanley S Zhang Kun K Fang Zhide Z

Bioinformatics (Oxford, England) 20121129 3

<h4>Motivation</h4>Normalization is critical in DNA copy number analysis. We propose a new method to correctly identify two-copy probes from the genome to obtain representative references for normalization in single nucleotide polymorphism arrays. The method is based on a two-state Hidden Markov Model. Unlike most currently available methods in the literature, the proposed method does not need to assume that the percentage of two-copy state probes is dominant in the genome, as long as there do e ...[more]

PMID: 23196989

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Project description:Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples. We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina’s proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300k version 1 and 2, 370k and 550k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations. The proposed normalization strategy represents a valuable low-level analysis tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies. To investigate the effects of a quantile normalization of Illumina Infinium data, compared to conventional normalization using BeadStudio (www.illumina.com), we renormalized 535 individual hybridizations conducted on Illumina 300K, 370K and 550K BeadChips. Sample types included breast cancer, colon cancer, urothelial carcinoma, leukemia as well as normal blood and HapMap samples. This series includes the 6 breast cancers hybridized on Illumina HumanHap 550K BeadChips.

Dataset Information

PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays.

Motivation

Results

Availability

Publications

PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays.

Similar Datasets

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