Normalization of Illumina Infinium Whole-genome SNP Data Improves Copy Number Estimates and Allelic Intensity Ratios

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2008 Oct 4

PMID 18831757

Citations 80

Authors

Johan Staaf

Johan Vallon-Christersson

David Lindgren

Gunnar Juliusson

Richard Rosenquist

Mattias Hoglund

Ake Borg

Markus Ringner

Affiliations

Soon will be listed here.

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.

Citing Articles

Parkinson's Disease Pathogenic Variants: Cross-Ancestry Analysis and Microarray Data Validation.

Hong S, Koretsky M, Lichtenberg J, Leonard H, Pitz V medRxiv. 2025; .

PMID: 39763553 PMC: 11702716. DOI: 10.1101/2024.12.16.24319097.

QTL identified that influence tuber length-width ratio, degree of flatness, tuber size, and specific gravity in a russet-skinned, tetraploid mapping population.

Park J, Whitworth J, Novy R Front Plant Sci. 2024; 15:1343632.

PMID: 38584948 PMC: 10996053. DOI: 10.3389/fpls.2024.1343632.

Identification of QTL associated with plant vine characteristics and infection response to late blight, early blight, and Verticillium wilt in a tetraploid potato population derived from late blight-resistant Palisade Russet.

Park J, Sathuvalli V, Yilma S, Whitworth J, Novy R Front Plant Sci. 2023; 14:1222596.

PMID: 37900754 PMC: 10600477. DOI: 10.3389/fpls.2023.1222596.

Preclinical evaluation of CDK4 phosphorylation predicts high sensitivity of pleural mesotheliomas to CDK4/6 inhibition.

Paternot S, Raspe E, Meiller C, Tarabichi M, Assie J, Libert F Mol Oncol. 2022; 18(4):866-894.

PMID: 36453028 PMC: 10994244. DOI: 10.1002/1878-0261.13351.

Construction of transgenic detection system of L. based on single nucleotide polymorphism chip.

Zhou E, Song N, Xiao Q, Farooq Z, Jia Z, Wen J 3 Biotech. 2021; 12(1):11.

PMID: 34966634 PMC: 8655060. DOI: 10.1007/s13205-021-03062-6.

References

Yang Y, Dudoit S, Luu P, Lin D, Peng V, Ngai J . Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 2002; 30(4):e15. PMC: 100354. DOI: 10.1093/nar/30.4.e15. View

Oosting J, Lips E, van Eijk R, Eilers P, Szuhai K, Wijmenga C . High-resolution copy number analysis of paraffin-embedded archival tissue using SNP BeadArrays. Genome Res. 2007; 17(3):368-76. PMC: 1800928. DOI: 10.1101/gr.5686107. View

Wang K, Li M, Hadley D, Liu R, Glessner J, Grant S . PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. Genome Res. 2007; 17(11):1665-74. PMC: 2045149. DOI: 10.1101/gr.6861907. View

Gunnarsson R, Staaf J, Jansson M, Ottesen A, Goransson H, Liljedahl U . Screening for copy-number alterations and loss of heterozygosity in chronic lymphocytic leukemia--a comparative study of four differently designed, high resolution microarray platforms. Genes Chromosomes Cancer. 2008; 47(8):697-711. DOI: 10.1002/gcc.20575. View

Barnes M, Freudenberg J, Thompson S, Aronow B, Pavlidis P . Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms. Nucleic Acids Res. 2005; 33(18):5914-23. PMC: 1258170. DOI: 10.1093/nar/gki890. View

Dunning M, Barbosa-Morais N, Lynch A, Tavare S, Ritchie M . Statistical issues in the analysis of Illumina data. BMC Bioinformatics. 2008; 9:85. PMC: 2291044. DOI: 10.1186/1471-2105-9-85. View

Khojasteh M, Lam W, Ward R, MacAulay C . A stepwise framework for the normalization of array CGH data. BMC Bioinformatics. 2005; 6:274. PMC: 1310623. DOI: 10.1186/1471-2105-6-274. View

Staaf J, Jonsson G, Ringner M, Vallon-Christersson J . Normalization of array-CGH data: influence of copy number imbalances. BMC Genomics. 2007; 8:382. PMC: 2190775. DOI: 10.1186/1471-2164-8-382. View

Greshock J, Feng B, Nogueira C, Ivanova E, Perna I, Nathanson K . A comparison of DNA copy number profiling platforms. Cancer Res. 2007; 67(21):10173-80. DOI: 10.1158/0008-5472.CAN-07-2102. View

10.

Peiffer D, Le J, Steemers F, Chang W, Jenniges T, Garcia F . High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome Res. 2006; 16(9):1136-48. PMC: 1557768. DOI: 10.1101/gr.5402306. View

11.

Gunderson K, Steemers F, Lee G, Mendoza L, Chee M . A genome-wide scalable SNP genotyping assay using microarray technology. Nat Genet. 2005; 37(5):549-54. DOI: 10.1038/ng1547. View

12.

Carvalho B, Bengtsson H, Speed T, Irizarry R . Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data. Biostatistics. 2006; 8(2):485-99. DOI: 10.1093/biostatistics/kxl042. View

13.

Assie G, LaFramboise T, Platzer P, Bertherat J, Stratakis C, Eng C . SNP arrays in heterogeneous tissue: highly accurate collection of both germline and somatic genetic information from unpaired single tumor samples. Am J Hum Genet. 2008; 82(4):903-15. PMC: 2427213. DOI: 10.1016/j.ajhg.2008.01.012. View

14.

Staaf J, Lindgren D, Vallon-Christersson J, Isaksson A, Goransson H, Juliusson G . Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays. Genome Biol. 2008; 9(9):R136. PMC: 2592714. DOI: 10.1186/gb-2008-9-9-r136. View

15.

Lin M, Wei L, Sellers W, Lieberfarb M, Wong W, Li C . dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data. Bioinformatics. 2004; 20(8):1233-40. DOI: 10.1093/bioinformatics/bth069. View

16.

Matsuzaki H, Dong S, Loi H, Di X, Liu G, Hubbell E . Genotyping over 100,000 SNPs on a pair of oligonucleotide arrays. Nat Methods. 2005; 1(2):109-11. DOI: 10.1038/nmeth718. View

17.

Steemers F, Chang W, Lee G, Barker D, Shen R, Gunderson K . Whole-genome genotyping with the single-base extension assay. Nat Methods. 2005; 3(1):31-3. DOI: 10.1038/nmeth842. View

18.

Pinkel D, Albertson D . Comparative genomic hybridization. Annu Rev Genomics Hum Genet. 2005; 6:331-54. DOI: 10.1146/annurev.genom.6.080604.162140. View

19.

Neuvial P, Hupe P, Brito I, Liva S, Manie E, Brennetot C . Spatial normalization of array-CGH data. BMC Bioinformatics. 2006; 7:264. PMC: 1523216. DOI: 10.1186/1471-2105-7-264. View

20.

Rajagopalan H, Lengauer C . Aneuploidy and cancer. Nature. 2004; 432(7015):338-41. DOI: 10.1038/nature03099. View