Methylated DNA immunoprecipitation sequencing data analysis software tools

An R package for comprehensive analysis of DNA methylation data obtained with any experimental protocol that provides single-CpG resolution, including Infinium 450K microarray and bisulfite sequencing protocols, but also MeDIP-seq and MBD-seq.

Allows analysis of enrichment-based epigenomic data. Repitools is an R package that provides several functions for quality assessment, visualization, summarization and statistical analysis of epigenomics experiments. The software utilizes aroma.affymetrix and several Bioconductor packages for various preprocessing steps. It includes for instance BayMeth for quantifying methylation. It was tested on Affymetrix and Nimblegen tiling microarrays and Illumina Genome Analyzer sequencing data.

Allows the prediction of absolute and relative methylation levels based on measures obtained by MeDIP-microarray experiments. MEDME is an experimental and analytical methodology designed to obtain enhanced estimates that better describe the true values of DNA methylation level throughout the genome.

Examines epigenomic and transcriptomic next generation sequencing (NGS) data. Octopus-toolkit can be used for antibody- or enzyme-mediated experiments and studies for the quantification of gene expression. It can accelerate the data mining of public epigenomic and transcriptomic NGS data for basic biomedical research. This tool provides a private and a public mode: one to process the user’s own data, and the other to analyze public NGS data by retrieving raw files from the GEO database.

Implements a statistical framework for modelling and transformation of MeDIP-seq enrichment data to absolute methylation levels similar to Bisulfite Sequencing (BS) read-outs. QSEA comprises functionality for data normalization that accounts for the effect of Copy Number Variations (CNVs) on the read-counts as well as for the detection and annotation of differentially methylated regions (DMRs). It is a reliable workflow for detecting aberrant methylation in patient cohorts. Results are strongly correlated with BS-seq data and DMRs can be confirmed by the literature as well as experimental validation.