A Systematic Evaluation of Cell-Type-Specific Differential Methylation Analysis in Bulk Tissue

Details

• Personal Author:
  Kuan PF ; Li S
• Description:
  We conducted a systematic assessment of computational models-CellDMC, TCA, HIRE, TOAST, and CeDAR-for detecting cell-type-specific differential methylation CpGs in bulk methylation data profiled using the Illumina DNA Methylation BeadArrays. This assessment was performed through simulations and case studies involving two epigenome-wide association studies (EWAS) on rheumatoid arthritis and major depressive disorder. Our evaluation provided insights into the strengths and limitations of each model. The results revealed that the models varied in performance across different metrics, sample sizes, and computational efficiency. Additionally, we proposed integrating the results from these models using the minimum p-value (minpv) and average p-value (avepv) approaches. Our findings demonstrated that these aggregation methods significantly improved performance in identifying cell-type-specific differential methylation CpGs. [Description provided by NIOSH]
• Subjects:
  Genetics Occupational Health Safety
• Keywords:
  Analytical Processes Author Keywords: DNA Methylation Bioinformatics Bulk Tissue Cell-type-specific Differential CpGs Cell Types DNA Damage Epigenetics EWAS Genomics
• ISSN:
  1477-4054
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  New York ; New York City Region [OSHA]
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  26
• Issue:
  2
• NIOSHTIC Number:
  nn:20070839
• Citation:
  Brief Bioinform 2025 Mar; 26(2):bbaf170
• Contact Point Address:
  Pei Fen Kuan, Department of Applied Mathematics and Statistics, Stony Brook University, Nicolls Road, 11794, New York, USA
• Email:
  peifen.kuan@stonybrook.edu
• Federal Fiscal Year:
  2025
• Performing Organization:
  State University of New York Stony Brook
• Peer Reviewed:
  True
• Start Date:
  20230701
• Source Full Name:
  Briefings in Bioinformatics
• End Date:
  20260630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:e558790992459e0348f9ae2a6363ff10a466287dfcb013ccb0c5473aa429869534d993eedc50b25a8c2e888804ea92193d745c815b115976290569004e9fd3b5
• Download URL:
  https://stacks.cdc.gov/view/cdc/208984/cdc_208984_DS1.pdf
• File Type:
  [PDF - 1.91 MB ]