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Related Experiment Video

Updated: Mar 23, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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An Efficient Approach to Screening Epigenome-Wide Data.

Meredith A Ray1, Xin Tong2, Gabrielle A Lockett3

  • 1Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Zach Curlin Street, Memphis, TN 38152, USA.

Biomed Research International
|April 2, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces ttScreening, an R package for identifying CpG DNA methylation sites associated with covariates. The method uses surrogate variable analysis (SVA) and nested validation, outperforming traditional approaches in simulations.

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Area of Science:

  • Genomics
  • Epigenetics
  • Biostatistics

Background:

  • High-dimensional screening of CpG DNA methylation sites is crucial for understanding complex biological associations.
  • Unaccounted variations and confounding effects can obscure true associations in methylation data.
  • Existing methods for multiple testing correction may lack sensitivity or specificity.

Purpose of the Study:

  • To develop and validate a robust method for screening CpG DNA methylation sites.
  • To account for unobserved confounding factors in methylation association studies.
  • To provide a user-friendly R package for efficient CpG site screening.

Main Methods:

  • Incorporation of surrogate variable analysis (SVA) into linear regressions (ordinary or robust).
  • Utilizing training and testing samples for nested validation.
  • Development of the ttScreening R package with efficient algorithms.

Main Results:

  • The proposed method demonstrates improved robustness and sensitivity compared to False Discovery Rate (FDR)-based and Bonferroni-based methods in simulations.
  • The approach shows potential for controlling both Type I and Type II errors.
  • Application to a large dataset identified CpG sites associated with maternal smoking.

Conclusions:

  • The ttScreening method offers a powerful and efficient approach for CpG site screening in epigenome-wide association studies.
  • SVA integration effectively adjusts for confounding effects, enhancing the reliability of identified CpG sites.
  • The ttScreening R package facilitates the application of this advanced methodology by researchers.