DNA methylation predictions

LGPL version 3

Download CpG island feature generator

We developed an application that is designed to generate LIBSVM formatted feature files for existing DNA methylation datasets, that allows users to distinguish between methylated and unmethylated CpG islands. The application can be used to read genomic locations with assigned numeric values. For example, read probe locations and intensities from DNA methylation experiments. Furthermore, the application can map the probes to overlapping CpG islands and lift locations between multiple human genome builds. For each of these locations, a LIBSVM compatible feature string is generated, that may include features, representing up to 15 categories. The user may choose the categories to generate features for. Furthermore, the application can generate support vector regression compatible files (by including the actual methylation values) or support vector classification compatible files (by converting given methylation intensities to binary states).
Afterwards, any machine learning approach can be applied to the generated features to create a model on those. The generated model can then be applied to novel data to predict, e.g., unknown methylation states of CpG islands.

File (Type) Size Version
  • CpG island feature generator
  • 10 MB 1.0.1 (2012-02-20)
  • Documentation
  • 250 KB 2012-02-17
  • Example input data for the application
  • <1 MB 2012-02-17


    Explore predicted data

    We predicted the DNA methylation status of CpG islands in various tissues¹. This webservice allows you to compare, download and visualize the experimental and predicted methylation landscape of various cell lines and tissues.


    Please select a tissue.



    Data sources:

    ¹ Clemens Wrzodek, Finja Büchel, Georg Hinselmann, Johannes Eichner, Florian Mittag, and Andreas Zell. Linking the epigenome to the genome: Correlation of different features to DNA methylation of CpG islands. PLoS ONE, 7(4):e35327, 04 2012. [ DOI | details | link | pdf ]

    ² Zhang Y, Rohde C, Tierling S, Jurkowski TP, Bock C, Santacruz D, Ragozin S, Reinhardt R, Groth M, Walter J, Jeltsch A: DNA Methylation Analysis of Chromosome 21 Gene Promoters at Single Base Pair and Single Allele Resolution. PLoS Genet 2009, 5(3)

    ³ Eckhardt F, Lewin J, Cortese R, Rakyan VK, Attwood J, Burger M, Burton J, Cox TV, Davies R, Down TA, Haefliger C, Horton R, Howe K, Jackson DK, Kunde J, Koenig C, Liddle J, Niblett D, Otto T, Pettett R, Seemann S, Thompson C, West T, Rogers J, Olek A, Berlin K, Beck S: DNA methylation profiling of human chromosomes 6, 20 and 22. Nat Genet 2006, 38(12):1378-1385