A collection of resources to filter 'bad' probes from the Illumina 450k and EPIC methylation arrays

Python toolkit for parsing, processing, and analysis of Illumina methylation array IDAT files

Regional Association of DNA Methylome variability with the Exposome and geNome (RAMEN) is an R package which goal is to identify Variable Methylated Loci (VML) in microarray DNA methylation data. Then, using genome (G) and exposome (E) data, it can identify which individual (G or E) or joint (G+E or GxE) model better explains the VML variability.

This package provides Illumina Mouse Methylation Array Manifest (12.v1, Genome Build mm10) compatible with minfi.

Gaussian mixture modelling - Unsupervised learning

Methylation Array Cross-Reactive Probes

📦 🔬 R/methyvim: Targeted, Robust, and Model-free Differential Methylation Analysis

Epicopy R package for CNV identification from methylation microarrays.

DNA methylation (DNAm) analysis using Illumina Methylation arrays (EPICv2, EPIC and 450K). It includes preprocessing, quality control, phenotype merging, and statistical modeling (GLM, LMM and nLME) for numerical and/or categorical phenotype using minfi, ENmix and wateRmelon frameworks.

generates reference matrix of average beta methylation values

Integrative analysis of differential DNA methylation and TFAP2α binding sites in non-small cell lung cancer using Illumina 450K microarrays and ChIP-seq data.

EpicopyData companion data package for Epicopy.

An annotation for mapping cpgs on the EPIC DNA methylation microarray platform to genomic features.

An algorithm made in R markdown that assures that the microarray is randomized without any bias.

📦 Bioconductor data package associated with the methyvim R package

Detection of rare aberrantly methylated regions / epimutations in array and NGS data — an R/Bioc package

MONTE:Methylation-based Observation Normalizationand Tumor purity Estimation

MONTE:Methylation-based Observation Normalizationand Tumor purity Estimation