EpiGRAPH: A user-friendly software for advanced (epi-) genome analysis and prediction
Welcome to EpiGRAPH!
EpiGRAPH is a software for genome and epigenome analysis. It was developed to help biomedical researchers making sense of large-scale datasets, which are nowadays routinely generated with technologies such as ChIP-on-chip, tiling microarrays and resequencing.
EpiGRAPH is both simple and powerful. For occasional users, the EpiGRAPH website provides a default analysis workflow that is applicable to most datasets. To find out more about any dataset of genomic regions, EpiGRAPH performs statistical analyses and applies powerful machine learning algorithms, based on a huge database of genome and epigenome information. For advanced users, EpiGRAPH allows full access to its standardized XML-based analysis and documentation system.
Things You Can Do with EpiGRAPH
Whenever you have a set of genomic regions, EpiGRAPH can help you to find out more about these regions and predict other regions of the same type in the genome.
For your inspiration, here are a few ideas for using EpiGRAPH that we find interesting (please also see the section below on the history of EpiGRAPH):
There will be a lot of other applications of EpiGRAPH, many of which we may not even have dreamt of.
Using, Extending, and Citing EpiGRAPH
EpiGRAPH is freely available to the scientific community (*). This includes not only the web service, but also the source code - in case you plan to set up a local copy, extend and tailor EpiGRAPH to your needs, or integrate parts of EpiGRAPH into your own software. Please write us an e-mail and we will provide you not only with the URL from where you can download the most recent source code release, but also with hints and help to get started adapting the source code to your objectives.
In order to support future work on extending and improving EpiGRAPH, it is important that you cite it whenever you use it. There are three references that are directly related to EpiGRAPH:
 Bock, C., K. Halachev, J. Büch and T. Lengauer (2008). "EpiGRAPH: Searching genomes and epigenomes with machine learning technology." http://epigraph.mpi-inf.mpg.de.
 Bock, C., M. Paulsen, S. Tierling, T. Mikeska, T. Lengauer and J. Walter (2006). "CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure." PLoS Genetics 2(3): e26.
 Bock, C., J. Walter, M. Paulsen and T. Lengauer (2007). "CpG island mapping by epigenome prediction." PLoS Computational Biology 3(6): e110.
The first citation refers to the web service and the public version of EpiGRAPH, and the other two citations describe the underlying concepts and methods. Typically, you would cite EpiGRAPH as follows: In the Results section, you could write: “We performed an EpiGRAPH  analysis on our dataset”, and in the Methods section, you could elaborate: “EpiGRAPH is a software for genome and epigenome analysis that was originally developed for predicting epigenetic information from the DNA [2, 3]. Here, we use the EpiGRAPH web service in order to analyze…”.
History and Future
EpiGRAPH has been applied in a number projects. Below, we give four examples that highlight different ways in which EpiGRAPH was used (and can be used).
Several other projects that involve EpiGRAPH analyses are currently in progress and will be added to this website in due time. In the future, we believe that EpiGRAPH may converge with other web services into a loosely coupled network of (epi-)genome analysis and data mining tools. Such a network would accept standardized XML-based analysis requests centrally and process them in a decentralized manner, with each web service contributing a specific analysis or access to a particular database. A descriptive term for this vision could be Statistical Genome Browser Network, and the standardized and extensible XML data format specified for EpiGRAPH may provide an appropriate internal language for data exchange within this network.
Developers and Contact
As any complex software package, EpiGRAPH is the product of many people who share the vision of a comprehensive and easy-to-use (epi-)genome analysis and prediction toolkit. Most of the development is currently performed by three people:
|Christoph Bock||Project leader, software architecture, database and middleware programming, frontend development||http://www.mpi-inf.mpg.de/~cbock|
|Konstantin Halachev||Backend and database programming, machine learning components||http://www.mpi-inf.mpg.de/~halachev|
|Joachim Büch||IT infrastructure, deployment, web server administration||http://www.mpi-inf.mpg.de/~buech|
Please feel free to contact any of us if you have questions, bug reports, ideas for future extensions or an interesting analysis that we should help you with. Typically, Christoph Bock will handle most requests.
(*) Free availability applies to universities and non-profit research institutes only. Companies should please contact us and will receive permission to use EpiGRAPH freely during an extended test phase.