The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
High-throughput DNA methylation profiling using universal bead arrays
Open accessAbstract
We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.
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.
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
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
DNA methylation patterns and epigenetic memory
Bird, A. (2002) · Genes & Development · doi:10.1101/gad.947102 · Cited by 7,124
Epigenetics in human disease and prospects for epigenetic therapy
Egger, G., Liang, G., Aparicio, A., & Jones, P. A. (2004) · Nature · doi:10.1038/nature02625 · Cited by 3,232
De novo quantitative bisulfite sequencing using the pyrosequencing technology
Dupont, J.-M., Tost, J., Jammes, H., & Gut, I. G. (2004) · Analytical Biochemistry · doi:10.1016/j.ab.2004.05.007 · Cited by 253
Cited by
DNA methylation landscapes: Provocative insights from epigenomics
Suzuki, M. M., & Bird, A. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2341 · Cited by 3,039
Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma
Noushmehr, H., Weisenberger, D. J., Diefes, K., Phillips, H. S., Pujara, K., Berman, B. P., Pan, F., Pelloski, C. E., Sulman, E. P., Bhat, K. P., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.03.017 · Cited by 2,337
Du, P., Zhang, X., Huang, C.-C., Jafari, N., Kibbe, W. A., Hou, L., & Lin, S. M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-587 · Cited by 2,136
Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome
Sandoval, J., Heyn, H., Moran, S., Serra-Musach, J., Pujana, M. A., Bibikova, M., & Esteller, M. (2011) · Epigenetics · doi:10.4161/epi.6.6.16196 · Cited by 990
Self-citationAge-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer
Teschendorff, A. E., Menon, U., Gentry-Maharaj, A., Ramus, S. J., Weisenberger, D. J., Shen, H., Campan, M., Noushmehr, H., Bell, C. G., Maxwell, A. P., et al. (2010) · Genome Research · doi:10.1101/gr.103606.109 · Cited by 855
Metadata
- Authors
- Bibikova, M., Lin, Z., Zhou, L., Chudin, E., Garcia, E. W., Wu, B., Doucet, D., Thomas, N. J., Wang, Y., Vollmer, E., Goldmann, T., Seifart, C., Jiang, W., Barker, D. L., Chee, M. S., Floros, J., & Fan, J.-B.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2006-01-31
- Volume
- 16
- Issue
- 3
- Pages
- 383-393
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2148405421
- Cited by
- 657
- References
- 4
- Type
- posted content
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: High-throughput DNA methylation profiling using universal bead arrays. https://app.cochat.ai/papers/10.1101/gr.4410706
- The paper
- Bibikova, M., Lin, Z., Zhou, L., Chudin, E., Garcia, E. W., Wu, B., Doucet, D., Thomas, N. J., Wang, Y., Vollmer, E., Goldmann, T., Seifart, C., Jiang, W., Barker, D. L., Chee, M. S., Floros, J., & Fan, J.-B. (2006). High-throughput DNA methylation profiling using universal bead arrays. Genome Research. https://doi.org/10.1101/gr.4410706
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
