Project »Genealyzer«

Web application for the analysis and comparison of gene expression data

© Adobe Stock
The Genealyzer project addresses the challenge of analyzing the increasing data volumes and making them comparable.

Gene expression profiling is a widely adopted method in areas like drug development or functional gene analysis. Microarray data of gene expression experiments is still commonly used and widely available for retrospective analyses. However, due to changes of the underlying technologies data sets from different technologies are often difficult to compare and thus a multitude of already available data becomes difficult to use.

The web application Genealyzer abstracts away mathematical and programmatical details in order to enable a convenient and customizable analysis of microarray data for large-scale reproducibility studies. In addition, the web application provides a feature that allows easy access to large microarray repositories.

Genealyzer consists of three basic steps which are necessary for a differential gene expression analysis as well as Gene Ontology (GO) enrichment analysis and the comparison of multiple analysis results. The web application can handle Affymetrix data as well as one-channel and two-channel Agilent data. All steps are visualized with meaningful plots. The application offers flexible analysis while being intuitively operable.

General Functionalities

© Fraunhofer ITEM
The Genealyzer application is build in three main modules. a) The data upload allows users to upload either raw files for both Affymetrix and Agilent (one- and two-channel) data sets or to directly access data sets uploaded within the Gene Expression Omnibus (GEO) database. b) Depending of on the technology the preprocessing module offers many different algorithms used for a variety of quality control tasks such as background correction and normalization all visualized in downloadable plots. c) Lastly, the Differential Gene Expression analysis can be can be calculated with users given parameters in mind.

Publication

Lietz, Kristina, Babak Saremi, and Lena Wiese. "Genealyzer: web application for the analysis and comparison of gene expression data." BMC bioinformatics 24.1 (2023): 150. Link (Open Access)

Contact

Lena Wiese

Contact Press / Media

Prof. Dr. Lena Wiese

Head of Attract Group Bioinformatics “IDA – intelligent data analysis for good health and chemical safety“

Phone +49 511 5350-303