Z Gastroenterol 2019; 57(01): e16-e17
DOI: 10.1055/s-0038-1677082
1. Basic Hepatology (Fibrogenesis, NPC, Transport)
Georg Thieme Verlag KG Stuttgart · New York

Hepamine 2.0

T Itzel
1   Division of Clinical Bioinformatics, Department of Internal Medicine II, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, Germany
,
M Evert
2   Department of Pathology, University of Regensburg, Germany
,
A Teufel
3   Division of Hepatology, Department of Internal Medicine II, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
04 January 2019 (online)

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Motivation:

Throughout the past two decades, numerous gene expression profiling data on literally all liver diseases were generated and stored in public databases. These data are thought to contain deep insights into the molecular development of liver diseases, support the development of molecular diagnostics and ultimately promote precision medicine in hepatology. However, once published the majority of these data remain idle. Only very few data were used for additional analyses or comparative projects by the hepatology research community. This may mostly be due to the limited bioinformatics knowledge on how to obtain and analyze the stored raw data by most biomedical research personnel. In order to overcome this barrier and to support an easy translation of bioinformatics data into translational hepatology research, we created Hepamine, a liver disease microarray database, visualization platform and data-mining resource.

Methods:

Microarray data were obtained from the ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress). Pre-analysis of expression data was performed using R statistical software and microarray analysis packages from the Bioconductor repository (https://www.bioconductor.org). Expression data were stored locally in a MySQL database.

Results:

We have generated Hepamine, a web-based repository of pre-analyzed microarray data for various liver diseases. Among these are HCC, CCC, liver fibrosis/cirrhosis, chronic hepatitis, autoimmune liver disease, fatty liver disease and many more. Further development was influenced by optimization the access and visualization of the data. By restructuring the frontend, the data access is know more comfortable. Filtering and visualization of the data are know configure able separatly. Genes may be searched on the basis of specific expression patterns across diverse samples. We also provide predefined gen sets to select pathways from KEGG and wikipathways. Results are furthermore visualized in simple three color tables indicating up-, down-, or no differential expression in multiple experiments. To enlarge the scope of the Hepamine, all data were linked to common functional and genetic databases, in particular offering information on the respective gene, signaling pathway analysis and evaluation of biological functions by means of gene ontologies.

Conculsion:

Hepamine provides comprehensive data and easy access to various hepatologic gene expression data. It will open this widely unused resource particularly to hepatologists without bioinformatics or microarray profiling experience and substantially facilitate the translation of these data to molecular hepatology research. Hepamine is accessible at: http://www.hepamine.de.