The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Evaluation of affinity-based genome-wide DNA methylation data: Effects of CpG density, amplification bias, and copy number variation
Abstract
DNA methylation is an essential epigenetic modification that plays a key role associated with the regulation of gene expression during differentiation, but in disease states such as cancer, the DNA methylation landscape is often deregulated. There are now numerous technologies available to interrogate the DNA methylation status of CpG sites in a targeted or genome-wide fashion, but each method, due to intrinsic biases, potentially interrogates different fractions of the genome. In this study, we compare the affinity-purification of methylated DNA between two popular genome-wide techniques, methylated DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain-based capture (MBDCap), and show that each technique operates in a different domain of the CpG density landscape. We explored the effect of whole-genome amplification and illustrate that it can reduce sensitivity for detecting DNA methylation in GC-rich regions of the genome. By using MBDCap, we compare and contrast microarray- and sequencing-based readouts and highlight the impact that copy number variation (CNV) can make in differential comparisons of methylomes. These studies reveal that the analysis of DNA methylation data and genome coverage is highly dependent on the method employed, and consideration must be made in light of the GC content, the extent of DNA amplification, and the copy number.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Individual group statistics were calculated using Mann and Whitney tests and corrected for multiple testing when necessary, according to the false discovery rate method previously described [48, 49].”
From The Resistin/TLR4/miR-155-5p axis: a novel signaling pathway in the onset of hypothalamic neuroinflammation (2025) · cites this paper as [48]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Jaenisch, R., & Bird, A. (2003) · Nature Genetics · doi:10.1038/ng1089 · Cited by 6,325
Human DNA methylomes at base resolution show widespread epigenomic differences
Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., Tonti-Filippini, J., Nery, J. R., Lee, L., Ye, Z., Ngo, Q.-M., et al. (2009) · Nature · doi:10.1038/nature08514 · Cited by 4,673
Genome-scale DNA methylation maps of pluripotent and differentiated cells
Meissner, A., Mikkelsen, T. S., Gu, H., Wernig, M., Hanna, J., Sivachenko, A., Zhang, X., Bernstein, B. E., Nusbaum, C., Jaffe, D. B., et al. (2008) · Nature · doi:10.1038/nature07107 · Cited by 2,536
Direct detection of DNA methylation during single-molecule, real-time sequencing
Flusberg, B. A., Webster, D. R., Lee, J. H., Travers, K. J., Olivares, E. C., Clark, T. A., Korlach, J., & Turner, S. W. (2010) · Nature Methods · doi:10.1038/nmeth.1459 · Cited by 1,460
CNV-seq, a new method to detect copy number variation using high-throughput sequencing
Xie, C., & Tammi, M. T. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-80 · Cited by 582
Research works printed but not linked: 43
- 2005, Amplification of whole tumor genomes and gene-by-gene mapping of genomic aberrations from limited sources of fresh-frozen and paraffin-embedded DNA, J Mol Diagn, 7, 171, 10.1016/S1525-1578(10)60543-0 · DOI
- 10.1038/nnano.2009.12 · DOI
- 10.1038/ncb2023 · DOI
- 10.1073/pnas.0806437105 · DOI
- 10.1038/nmeth.1414 · DOI
- 10.1093/nar/gng015 · DOI
- 10.1101/gr.7301508 · DOI
- 10.1186/gb-2008-9-8-231 · DOI
- 10.1073/pnas.0601180103 · DOI
- 10.1101/gr.7080508 · DOI
- 10.1016/S0168-9525(98)01636-9 · DOI · Paper page
- 2002, The fundamental role of epigenetic events in cancer, Natl Rev, 3, 415, 10.1038/nrg816 · DOI · Paper page
- 10.1016/j.cell.2007.01.029 · DOI · Paper page
- 10.1038/ng.286 · DOI
- 10.1038/nrg2732 · DOI
- 10.1186/gb-2009-10-3-r25 · DOI · Paper page
- Li N , Ye M , Li Y , Yan Z , Butcher LM , Sun J , Han X , Chen Q , Zhang X , Wang J . 2010. Whole genome DNA methylation analysis based on high throughput sequencing technology. Methods (in press). doi: 10.1016/j.ymeth.2010.04.009. · DOI
- 10.1093/nar/22.24.5354 · DOI
- 10.1002/jcb.10740 · DOI
- 10.1158/0008-5472.CAN-08-1419 · DOI
- 10.1093/nar/gkp260 · DOI
- 10.1007/978-1-60327-192-9_7 · DOI
- 10.1101/gr.080721.108 · DOI
- 10.1093/nar/gkn735 · DOI
- 10.1093/nar/gkn378 · DOI
- 10.1158/0008-5472.CAN-06-1888 · DOI
- 10.1073/pnas.0710735105 · DOI
- 10.1126/science.290.5500.2306 · DOI
- 10.1093/bioinformatics/btp616 · DOI · Paper page
- 10.1186/1471-2164-11-137 · DOI
- 10.1093/nar/gkp992 · DOI · Paper page
- 10.1038/sj.onc.1205153 · DOI
- 10.1091/mbc.E10-01-0018 · DOI
- 10.1093/bioinformatics/btq247 · DOI
- 10.1126/science.1136678 · DOI
- 10.1038/nmeth0408-279 · DOI
- 10.1371/journal.pone.0006700 · DOI
- 10.1371/journal.pone.0005241 · DOI
- 10.1038/ng1598 · DOI
- 10.1038/ng1990 · DOI
- 10.1093/nar/gkn133 · DOI
- 10.1007/978-1-60327-378-7_10 · DOI
- 10.2144/000113203 · DOI
Cited by
Sorted by citations
McCarthy, D. J., Chen, Y., & Smyth, G. K. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks042 · Cited by 5,195
The signature of maternal rearing in the methylome in rhesus macaque prefrontal cortex and T cells
Provençal, N., Suderman, M. J., Guillemin, C., Massart, R., Ruggiero, A., Wang, D., Bennett, A. J., Pierre, P. J., Friedman, D. P., Côté, S. M., et al. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.1470-12.2012 · Cited by 312
Childhood abuse is associated with methylation of multiple loci in adult DNA
Suderman, M., Borghol, N., Pappas, J. J., Pinto Pereira, S. M., Pembrey, M., Hertzman, C., Power, C., & Szyf, M. (2014) · BMC Medical Genomics · doi:10.1186/1755-8794-7-13 · Cited by 193
Provençal, N., Suderman, M. J., Guillemin, C., Vitaro, F., Côté, S. M., Hallett, M., Tremblay, R. E., & Szyf, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089839 · Cited by 85
Prévost, M., Crépin, D., Rifai, S. A., Poizat, G., Gonçalves, M., van Barneveld, F., Shadpay, R., Taouis, K., Riffault, L., Benomar, Y., et al. (2025) · Journal of Neuroinflammation · doi:10.1186/s12974-025-03522-3 · Cited by 19
Metadata
- Authors
- Robinson, M. D., Stirzaker, C., Statham, A. L., Coolen, M. W., Song, J. Z., Nair, S. S., Strbenac, D., Speed, T. P., & Clark, S. J.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2010-11-02
- Volume
- 20
- Issue
- 12
- Pages
- 1719-1729
- ISSN
- 1088-9051
- Cited by
- 114
- References
- 5
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
