Detection of cell-type-specific risk-CpG sites in epigenome-wide association studies
Abstract
In epigenome-wide association studies, the measured signals for each sample are a mixture of methylation profiles from different cell types. The current approaches to the association detection only claim whether a cytosine-phosphate-guanine (CpG) site is associated with the phenotype or not, but they cannot determine the cell type in which the risk-CpG site is affected by the phenotype. Here, we propose a solid statistical method, HIgh REsolution (HIRE), which not only substantially improves the power of association detection at the aggregated level as compared to the existing methods but also enables the detection of risk-CpG sites for individual cell types.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 29
- FWCI
- 1.49
- Field percentile
- top 18%
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Cell-type specific EWAS identifies genes involved in HIV pathogenesis andoncogenesis among people with chronic HIV infection
- Identification of differentially methylated cell-types in Epigenome-Wide Association Studies
Shijie Zheng, Charles E. Breeze, … Andrew Erich Teschendorff·Nature MethodsPeer-reviewed·Nov 19, 2018
- Cell type-specific signal analysis in EWAS
Charles E. Breeze·bioRxiv·May 21, 2021
- Integrating genome and epigenome data to identify tissue-specific DNA methylation biomarkers for cancer risk
Yaohua Yang, Yaxin Chen, … Jirong Long·medRxiv·Aug 9, 2023
- Deconvolution-based cell-type specific DNA methylation-wide and transcriptome-wide association studies identify risk CpG sites and genes associated with colorectal cancer risk
Qing Li, Lili Xu, … Xingyi Guo·medRxiv·Jun 12, 2026
- Correcting For Cell-Type Heterogeneity In Epigenome-Wide Association Studies: Premature Analyses And Conclusions
Shijie Zheng, Stephan Beck, … Andrew Erich Teschendorff·bioRxiv·Mar 28, 2017