charm

charm analyzes DNA methylation data from NimbleGen microarrays produced with the McrBC restriction enzyme protocol to identify differential methylation and estimate percentage methylation across samples.

Key Features:

• Differential Methylation Analysis: Identifies differentially methylated regions (DMRs) between sample groups such as normal versus tumor tissues or different tissue types.
• Normalization Strategy: Implements a normalization strategy tailored to NimbleGen microarray-based DNA methylation data to address violations of expression-array assumptions (e.g., non-uniform signal distribution).
• Empirical Bayes Percentage Methylation Estimator: Applies an empirical Bayes approach to estimate percentage methylation while accounting for systematic errors and unwanted variability in microarray measurements.
• Array Quality Assessment Tools: Provides tools to assess NimbleGen microarray data quality prior to downstream analysis.

Scientific Applications:

• Cancer and disease epigenetics: Enables investigation of epigenetic modifications associated with cancer and other diseases through genome-wide methylation profiling.
• Tissue-specific methylation profiling: Supports characterization of tissue-specific methylation patterns to elucidate gene regulation mechanisms.
• Biomarker identification: Facilitates comparison of normal versus pathological samples to identify potential methylation biomarkers for diagnosis or prognosis.

Methodology:

Processes NimbleGen microarray data generated with McrBC digestion (which selectively cuts unmethylated DNA), applies a tailored normalization strategy, computes percentage methylation using an empirical Bayes estimator, performs array quality assessment, and identifies differentially methylated regions between sample groups.