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Related Concept Videos

Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

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Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
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Related Experiment Video

Updated: Sep 24, 2025

DNA Methylation: Bisulphite Modification and Analysis
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DNA Methylation Imputation Across Platforms.

Gang Li1, Guosheng Zhang2,1,3, Yun Li4,5

  • 1Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Methods in Molecular Biology (Clifton, N.J.)
|May 3, 2022
PubMed
Summary
This summary is machine-generated.

This study reviews DNA methylation imputation, introducing a penalized functional regression (PFR) method for across-platform imputation. The PFR method enhances statistical power for epigenome-wide association studies using DNA methylation data.

Keywords:
DNA methylation imputationEpigenome-wide association studyEpigenomic imputationPenalized functional regression

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Methodology for Accurate Detection of Mitochondrial DNA Methylation
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Area of Science:

  • Genomics
  • Epigenetics
  • Computational Biology

Background:

  • DNA methylation is crucial for gene regulation and cellular function.
  • Imputation of DNA methylation data is essential for integrating diverse datasets and increasing statistical power.
  • Existing statistical and computational methods have limitations in handling across-platform DNA methylation data.

Purpose of the Study:

  • To provide a comprehensive review of DNA methylation imputation.
  • To introduce and detail a novel penalized functional regression (PFR) method for across-platform DNA methylation imputation.
  • To demonstrate the utility of the PFR method using real-world data, such as the acute myeloid leukemia (AML) dataset from The Cancer Genome Atlas (TCGA).

Main Methods:

  • A penalized functional regression (PFR) framework is employed for imputation.
  • The method incorporates nonlocal information for improved imputation accuracy.
  • Data harmonization, model building, quality filtering, and assessment are key components of the PFR method.

Main Results:

  • The PFR method demonstrates strong performance in both simulated data and the TCGA AML dataset.
  • The PFR model effectively handles across-platform DNA methylation data.
  • The method significantly boosts statistical power for subsequent epigenome-wide association studies.

Conclusions:

  • The developed penalized functional regression model is a valuable tool for across-platform DNA methylation imputation.
  • This method enhances the integration and analysis of diverse DNA methylation datasets.
  • Future research should explore advanced imputation techniques for DNA methylation data.