methylumi

methylumi processes Illumina methylation microarray data to manage raw and processed methylation measurements and enable preprocessing, normalization, and quality assessment for DNA methylation analysis.

Key Features:

• Data Management: Provides eSet-derived classes to store sample and feature information, supports MIAME, and holds multiple matrices of methylation data.
• Data Import: Offers methylumiR to read Illumina text files into a MethyLumiSet and methylumIDAT to process raw IDAT files from HumanMethylation27 and HumanMethylation450 arrays.
• Preprocessing and Quality Control: Implements background correction, normalization, and quality-control functions to reduce variance and improve detection of subtle methylation changes.
• Normalization: Supports separate normalization of methylated (M) and unmethylated (U) signal intensities and provides quantile normalization schemes appropriate for the HumanMethylation450 BeadChip.
• Quality Assessment: Uses metrics based on genomic imprinting, X-chromosome inactivation (XCI), and SNP genotyping probes on the array as quality scores and tests of normalization.
• Integration and Compatibility: Integrates with R packages such as wateRmelon, minfi, and IMA to apply consistent normalization methods and data-quality tests across workflows.

Scientific Applications:

• Epigenetic Research: Enables characterization of genome-wide DNA methylation landscapes across tissues, developmental stages, and experimental conditions.
• Disease Pathogenesis: Facilitates detection of small absolute changes in DNA methylation associated with complex disease phenotypes.

Methodology:

Performs background correction, various normalization schemes including separate normalization of methylated (M) and unmethylated (U) intensities and quantile normalization, and quality assessment using imprinting, X-chromosome inactivation, and SNP-genotype–derived metrics.