Hepamine – A Liver Disease Microarray Database, Visualization Platform and Data-Mining Resource

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, viral hepatitis, autoimmune liver disease, fatty liver disease, liver regeneration, and biliary atresia. At its initial release Hepamine contains more than 25 gene expression datasets or relevant subsets. A self-explanatory website offers open and easy access to the respective gene expression profiles and support to compare samples, experiments and various liver diseases. Results are visualized in simple three color tables indicating up-, down-, or no differential expression in multiple experiments. In addition the user is able to obtain the corresponding values in detail. 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.