gms | German Medical Science

MAINZ//2011: 56. GMDS-Jahrestagung und 6. DGEpi-Jahrestagung

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V.
Deutsche Gesellschaft für Epidemiologie e. V.

26. - 29.09.2011 in Mainz

Leukemia Gene Atlas – A platform to support research and analysis of molecular data of leukemias

Meeting Abstract

  • Katja Hebestreit - Westfälische Wilhelms-Universität Münster, Münster
  • Sören Gröttrup - Westfälische Wilhelms-Universität Münster, Münster
  • Christian Ruckert - Westfälische Wilhelms-Universität Münster, Münster
  • Hans-Ulrich Klein - Westfälische Wilhelms-Universität Münster, Münster
  • Martin Dugas - Westfälische Wilhelms-Universität Münster, Münster

Mainz//2011. 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi). Mainz, 26.-29.09.2011. Düsseldorf: German Medical Science GMS Publishing House; 2011. Doc11gmds089

doi: 10.3205/11gmds089, urn:nbn:de:0183-11gmds0899

Published: September 20, 2011

© 2011 Hebestreit et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Background: The Leukemia Gene Atlas (LGA) was designed to provide a tool for retrieval of relevant genes, results and studies regarding genomic leukemia data and for the analysis of these data. The LGA supplements conventional repositories, such as GEO [1], ArrayExpress [2] and Oncomine [3], because of its variety of integrated data types and, more importantly, of its leukemia specific biological and medical annotations. A first version went online in December 2010:

Methods: The central part of the LGA is a database storing the molecular data of published studies, as well as results, such as gene signatures, GO terms or lists of mutations. The samples associated with the molecular data were classified and annotated leukemia specifically according to their biological and clinical characteristics. The database is publicly available via a website which supports the search and selection of studies and samples with comprehensive search functions. The website also provides a wide range of visualization and analysis tools to process the stored data. An exceptional implement is the search in published result tables which supports, for example, the search for studies and groups of samples whose gene expression patterns significantly differ for certain genes of interest.

Results: The LGA supports the research of published data and hence the interpretation of newly measured data. Currently, the database stores 293 result tables and the data of 5,000 samples from nine studies and four data types (gene expression, methylation, genotypes and next-generation sequencing). We intend to integrate many further data sets and thus to increase its versatility and usability.


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