Quantitative cross-validation and content analysis of the 450k DNA methylation array from Illumina, Inc.
Open accessAbstract
Background: The newly released 450k DNA methylation array from Illumina, Inc. offers the possibility to analyze more than 480,000 individual CpG sites in a user friendly standardized format. In this study the relationship between the β-values provided by the Illumina, Inc. array for each individual CpG dinucleotide and the quantitative methylation levels obtained by pyrosequencing were analyzed. In addition, the representation of microRNA genes and imprinted loci on the Illumina, Inc. array was assessed in detail. Genomic DNA from 4 human breast cancer cell lines (IPH-926, HCC1937, MDA-MB-134, PMC42) and 18 human breast cancer specimens as well as 4 normal mammary epithelial fractions was analyzed on 450k DNA methylation arrays. The β-values for 692 individual CpG sites from 62 different genes were cross-validated using conventional quantitative pyrosequencing. Findings: The newly released 450k methylation array from Illumina, Inc. shows a high concordance with quantitative pyrosequencing if identical CpG sites are analyzed in cell lines (Spearman r = 0.88, p ≪ 0.0001), which is somewhat reduced in primary tumor specimens (Spearman r = 0.86, p ≪ 0.0001). 80.7% of the CpG sites show an absolute difference in methylation level of less than 15 percentage points. If different CpG sites in the same CpG islands are targeted the concordance is lower (r = 0.83 in cell lines and r = 0.7 in primary tumors). The number of CpG sites representing microRNA genes and imprinted loci is very heterogeneous (range: 1 – 70 CpG sites for microRNAs and 1 – 288 for imprinted loci). Conclusions: The newly released 450k methylation array from Illumina, Inc. provides a genome-wide quantitative representation of DNA methylation aberrations in a convenient format. Overall, the congruence with pyrosequencing data is very good. However, for individual loci one should be careful to translate the β-values directly into percent methylation levels.
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Profile correlations are insensitive to normalization problems because they are dominated by the majority of probes that do not show true differences.
“Profile correlations are also insensitive to the potential problems of normalization because they are dominated by the majority of probes which do not show true differences”
From A data-driven approach to preprocessing Illumina 450K methylation array data (2013) · cites this paper as [14]
In Findings > Cross-validation of 450k methylation array and pyrosequencing (page not provided), the paper says correlations can be misleading because data points cluster near 0% and 100% methylation, masking poorer agreement in the middle range. It does not say this makes profile correlations insensitive to normalization problems, or that the dominant probes are those without true differences. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe minority of intermediate methylation values are susceptible to greater changes after normalization but are overlooked by a correlation test.
“the minority of intermediate methylation values would be susceptible to far greater changes after normalization but would be overlooked by a correlation test [14]”
From A data-driven approach to preprocessing Illumina 450K methylation array data (2013) · cites this paper as [14]
In Findings > Cross-validation of 450k methylation array and pyrosequencing (page not specified), the paper says correlation coefficients can be misleading because values near 0% and 100% dominate, masking poorer agreement at intermediate methylation levels. It compares array measurements with pyrosequencing; it does not say that intermediate values undergo greater changes after normalization. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe majority of CpG sites assayed are fully methylated or fully unmethylated and would change little after normalization.
“the majority of CpG sites assayed are in a fully methylated or fully unmethylated state and would change little after normalization”
From A data-driven approach to preprocessing Illumina 450K methylation array data (2013) · cites this paper as [14]
The Conclusion says that β-values are a good measure of methylation status for most CpG sites, but it does not say most sites are fully methylated or fully unmethylated. The Findings discuss agreement with pyrosequencing, not changes after normalization. Searches for extreme methylation states and normalization found no passage addressing the claim. (LLM, conf=0.72)
Experimental — accuracy not yet measured
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- Authors
- Roessler, J., Ammerpohl, O., Gutwein, J., Hasemeier, B., Anwar, S. L., Kreipe, H., & Lehmann, U.
- Affiliations
- Medizinische Hochschule Hannover (DE)
- University Hospital Schleswig-Holstein (DE)
- Corresponding author
- Lehmann, Ulrich
- Venue
- BMC Research Notes
- Published
- 2012-04-30
- Volume
- 5
- Issue
- 1
- Pages
- 210-210
- ISSN
- 1756-0500 (ISSN-L)
- PMC
- PMC3420245
- OpenAlex
- W2097998761
- Cited by
- 112
- References
- 24
- Citations by year
- 2026: 3 · 2024: 1 · 2023: 1 · 2022: 4 · 2021: 11 · 2020: 2 · 2019: 9 · 2018: 10 · 2017: 10 · 2016: 15 · 2015: 18 · 2014: 9 · 2013: 15 · 2012: 4
- FWCI
- 5.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Research Notes (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (SFB TRR77, Project B1, TRR77)
- Deutsche Krebshilfe
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Syndromes and Imprinting
- Keywords
- DNA methylation, 450k methylation array, pyrosequencing, CpG sites, breast cancer, microRNA genes, genomic imprinting, imprinted loci, CpG islands, mammary epithelial cells
- MeSH terms
- Breast Neoplasms, Female, Humans, Reproducibility of Results, Sequence Analysis, DNA, Genomic Imprinting, DNA Methylation, Base Pairing, Cell Line, Tumor, snRNP Core Proteins, Genetic Loci
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