ArticleScientific reports2015
Genome-wide DNA methylation detection by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- DNA methylation biomarkers-based pan-cancer classifier: predictive modeling for cancer classification.Genome medicine · 2026Article
- Refinement of prognostication for IDH-mutant astrocytomas using DNA methylation-based classification.Brain pathology (Zurich, Switzerland) · 2024Article
- Article
- Improving Infinium MethylationEPIC data processing: re-annotation of enhancers and long noncoding RNA genes and benchmarking of normalization methods.Epigenetics · 2022Article
- Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma.Journal of experimental & clinical cancer research : CR · 2022Article
- Immune cell deconvolution of bulk DNA methylation data reveals an association with methylation class, key somatic alterations, and cell state in glial/glioneuronal tumors.Acta neuropathologica communications · 2021Article
- In Response to Abiotic Stress, DNA Methylation Confers EpiGenetic Changes in Plants.Plants (Basel, Switzerland) · 2021Review
- Targeting DNA Methylation Depletes Uterine Leiomyoma Stem Cell-enriched Population by Stimulating Their Differentiation.Endocrinology · 2020Article
- Integrating DNA methylation measures to improve clinical risk assessment: are we there yet? The case of BRCA1 methylation marks to improve clinical risk assessment of breast cancer.British journal of cancer · 2020Review
- Increased presence and differential molecular imprinting of transit amplifying cells in psoriasis.Journal of molecular medicine (Berlin, Germany) · 2020Article
- Gene promoter and exon DNA methylation changes in colon cancer development - mRNA expression and tumor mutation alterations.BMC cancer · 2018Article
- Profiling DNA methylation differences between inbred mouse strains on the Illumina Human Infinium MethylationEPIC microarray.PloS one · 2018Article
- Article
- Aberrant DNA methylation of WNT pathway genes in the development and progression of CIMP-negative colorectal cancer.Epigenetics · 2016Article
- DNA methylation-based deconvolution study of glioblastoma heterogeneity and identification of cell compositions associated with patient survival.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). Objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples, i.e. 65 glioblastoma and 5 non-tumoral tissues. As MethylCap-seq coverages were limited, we focused on the inherent capacity of the methodology to detect methylated loci rather than a quantitative analysis. MethylCap-seq and HM450 data were dichotomized and performances were compared using a gold standard free Bayesian modelling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. In addition, genome-wide characteristics were compared, revealing that HM450 probes identified substantially fewer regions compared to MethylCap-seq. Although results indicated that the latter method can detect more potentially relevant DNA-methylation, this did not translate into the discovery of more differentially methylated loci between tumours and controls compared to HM450. Our results therefore indicate that both methodologies are complementary, with a higher sensitivity for HM450 and a far larger genome-wide coverage for MethylCap-seq, but also that a more comprehensive character does not automatically imply more significant results in biomarker studies.
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