Max Planck Institute for Molecular Genetics
Max Planck Institute for Molecular Genetics - Ihnestraße 73 - 14195 Berlin - Germany - Phone: (+49 30) 8413 0 - Fax: (+49 30) 8413 1388
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Introduction

MEDIPS package and manual

MeDIP-seq stem cell data

Microarray stem cell data


MEDIPS
Software for the analysis of MeDIP-seq data
Introduction
The MEDIPS software package was developed for analyzing data derived from methylated DNA immunoprecipitation (MeDIP) experiments followed by sequencing (MeDIP-seq). Nevertheless, functionalities like the saturation analysis may be applied to other types of sequencing data (e.g. ChIP-seq).

MEDIPS was presented in the publication Chavez et al., Computational analysis of genome-wide DNA methylation during the differentiation of human embryonic stem cells along the endodermal lineage, Genome Res. 2010 Oct;20(10):1441-50. Epub 2010 Aug 27 (PMID: 20802089).

MEDIPS simplifies the processing of MeDIP-seq data as it starts where the mapping tools stop and allows for exporting of the results for visualization in common genome browsers. MEDIPS is available as an Rlibrary, is suitable for any arbitrary genome available via Bioconductors annotation libraries and provides further functionalities for an accelerated and comprehensive processing of MeDIP-seq data.

The main features of the package are:

  • calculating genome wide MeDIP-seq signal densities at a user specified resolution,
  • estimating the reproducibilty for obtaining full genome methylation profiles with respect to the total number of given short reads and with respect to the size of the reference genome,
  • analyzing the coverage of genome wide DNA sequence pattern (e.g. CpGs) by the given reads,
  • calculating CpG enrichment factors as a quality control for the immuno-precipitation,
  • calculating genome wide sequence pattern densities (e.g. CpGs) at a user specied resolution,
  • plotting of calibration plots as a data quality check and for a visual inspection of the dependency between local sequence pattern (e.g. CpG) densities and MeDIP-seq signals,
  • normalization of MeDIP-seq data with respect to local sequence pattern (e.g. CpG) densities,
  • summarized methylation values for genome wide windows of a specified length or for user supplied regions of interest (ROIs),
  • calculation of differential methylation on raw or normalized data comparing two sets of MeDIP-seq data with respect to Input-seq data,
  • export raw and normalized data for visualization in common genome browsers (e.g. the UCSC genome browser),
  • annotation of identified differentially methylated regions (DMRs) with respect to given annotation files containing genomic coordinates of e.g. promoter regions, exons, introns, CpG islands, etc.
The package comes along with a manual (version 1.0.0) describing all steps of the workow.