Methodology article

Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios

Johan Staaf^1,2 , Johan Vallon-Christersson^1,2 , David Lindgren¹ , Gunnar Juliusson³ , Richard Rosenquist⁴ , Mattias Höglund¹ , Åke Borg^1,2,3 and Markus Ringnér^1,2

¹Department of Oncology, Clinical Sciences, Lund University, SE-22185 Lund, Sweden

²CREATE Health Strategic Centre for Clinical Cancer Research, Lund University, SE-22184 Lund, Sweden

³Lund Strategic Research Center for Stem Cell Biology and Cell Therapy, Lund University, SE-22184 Lund, Sweden

⁴Department of Genetics and Pathology, Uppsala University, SE-75185 Uppsala, Sweden

author email corresponding author email

BMC Bioinformatics 2008, 9:409doi:10.1186/1471-2105-9-409

Published:	2 October 2008

Abstract

Background

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.

Results

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 300 k version 1 and 2, 370 k and 550 k 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.

Conclusion

The proposed normalization strategy represents a valuable tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.