ArticleEURASIP journal on bioinformatics & systems biology2013
Identification of thresholds for dichotomizing DNA methylation data.
Article in EURASIP journal on bioinformatics & systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Article
- Long non-coding RNA CCAT1 acts as an oncogene to promote radiation resistance in lung adenocarcinoma: an epigenomics-based investigation.Functional & integrative genomics · 2024Article
- Vector genome loss and epigenetic modifications mediate decline in transgene expression of AAV5 vectors produced in mammalian and insect cells.Molecular therapy : the journal of the American Society of Gene Therapy · 2022Article
- Prognostic Implications and Immune Infiltration Characteristics of Chromosomal Instability-Related Dysregulated CeRNA in Lung Adenocarcinoma.Frontiers in molecular biosciences · 2022Article
- Methylation of CpG Sites as Biomarkers Predictive of Drug-Specific Patient Survival in Cancer.Cancer informatics · 2022Article
- Distributional changes in gene-specific methylation associated with temperature.Environmental research · 2016Article
- Genome-scale methylation assessment did not identify prognostic biomarkers in oral tongue carcinomas.Clinical epigenetics · 2016Article
- Connexin 30 expression inhibits growth of human malignant gliomas but protects them against radiation therapy.Neuro-oncology · 2015Article
- Quantitative methodology is critical for assessing DNA methylation and impacts on correlation with patient outcome.Clinical epigenetics · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
: DNA methylation plays an important role in many biological processes by regulating gene expression. It is commonly accepted that turning on the DNA methylation leads to silencing of the expression of the corresponding genes. While methylation is often described as a binary on-off signal, it is typically measured using beta values derived from either microarray or sequencing technologies, which takes continuous values between 0 and 1. If we would like to interpret methylation in a binary fashion, appropriate thresholds are needed to dichotomize the continuous measurements. In this paper, we use data from The Cancer Genome Atlas project. For a total of 992 samples across five cancer types, both methylation and gene expression data are available. A bivariate extension of the StepMiner algorithm is used to identify thresholds for dichotomizing both methylation and expression data. Hypergeometric test is applied to identify CpG sites whose methylation status is significantly associated to silencing of the expression of their corresponding genes. The test is performed on either all five cancer types together or individual cancer types separately. We notice that the appropriate thresholds vary across different CpG sites. In addition, the negative association between methylation and expression is highly tissue specific.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.