IMAGE_R

IMAGE_R maps methylation quantitative trait loci (mQTLs) in bisulfite sequencing data to detect genetic variants associated with DNA methylation variation.


Key Features:

  • Statistical methodology: Employs a statistical model tailored for mQTL mapping that accommodates the count nature of bisulfite sequencing data.
  • Allele-specific analysis: Integrates allele-specific methylation patterns from heterozygous individuals to increase precision and power of mQTL detection.
  • Comparative performance: Demonstrates, via extensive simulation studies, identification of a greater number of mQTLs compared with other existing approaches.
  • R package implementation: Provided as an implementation in R for analysis of sequencing-based methylation data.

Scientific Applications:

  • mQTL mapping: Applied to bisulfite sequencing studies to map genetic variants associated with DNA methylation levels.
  • Genotype–epigenotype associations: Used to elucidate interactions between genetic variants and allele-specific DNA methylation that may influence genotype–trait associations.
  • Epigenetic studies of traits and disease: Facilitates investigation of epigenetic mechanisms underlying phenotypic traits and diseases.

Methodology:

Models the count-based nature of bisulfite sequencing data and integrates allele-specific methylation from heterozygous individuals, with performance assessed through extensive simulation studies.

Topics

Details

License:
GPL-2.0
Tool Type:
library
Programming Languages:
R, C++
Added:
1/9/2020
Last Updated:
1/14/2021

Operations

Publications

Fan Y, Vilgalys TP, Sun S, Peng Q, Tung J, Zhou X. IMAGE: high-powered detection of genetic effects on DNA methylation using integrated methylation QTL mapping and allele-specific analysis. Genome Biology. 2019;20(1). doi:10.1186/s13059-019-1813-1. PMID:31651351. PMCID:PMC6813132.

PMID: 31651351
PMCID: PMC6813132
Funding: - National Institutes of Health: R01HD088558, R01HG009124 - National Science Foundation: BCS1751783, DMS1712933 - North Carolina Biotechnology Center: 2016-IDG-1013

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