MAGAR

MAGAR computes methylation quantitative trait loci (methQTL) from matched DNA methylation and genotyping data using a linear modeling strategy that accounts for the local correlation structure of CpGs.

Key Features:

• methQTL Identification: MAGAR calls CpGs/SNPs that are methQTLs from matched genotyping and DNA methylation data.
• Cell Type-Specific methQTL Detection: MAGAR discriminates common methQTLs from cell type-specific methQTL effects.
• Correlation Structure Accounting: MAGAR accounts for the local correlation structure of CpGs in its modeling approach.

Scientific Applications:

• Tissue-Specific Epigenomic Variation Analysis: MAGAR enables systematic analysis of genetic variant influences on cell type-specific epigenomic variation across multiple tissues and cell types including ileum, rectum, T cells, and B cells.
• Enhancer Element Localization: MAGAR can identify cell type-specific methQTLs preferentially located in enhancer elements.
• Gene-Specific methQTL Validation: MAGAR supports validation of methQTLs located in specific genes such as PON1, ZNF155, and NRG2 through integration with ultra-deep local sequencing data.

Methodology:

MAGAR employs a two-step computational framework using linear modeling to identify methQTLs. The method accounts for the local correlation structure of CpGs and supports discrimination of common from cell type-specific methQTL effects.