GeneTrail: A Framework for the Analysis of High-Throughput Profiles

• Main Authors: Nico Gerstner, Tim Kehl, Kerstin Lenhof, Lea Eckhart, Lara Schneider, Daniel Stöckel, Christina Backes, Eckart Meese, Andreas Keller, Hans-Peter Lenhof
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-09-01
• Series: Frontiers in Molecular Biosciences
• Subjects: COVID-19; enrichment analysis; gene regulation; web server; time-serie analysis; single-cell analysis
• Online Access: https://www.frontiersin.org/articles/10.3389/fmolb.2021.716544/full

Experimental high-throughput techniques, like next-generation sequencing or microarrays, are nowadays routinely applied to create detailed molecular profiles of cells. In general, these platforms generate high-dimensional and noisy data sets. For their analysis, powerful bioinformatics tools are required to gain novel insights into the biological processes under investigation. Here, we present an overview of the GeneTrail tool suite that offers rich functionality for the analysis and visualization of (epi-)genomic, transcriptomic, miRNomic, and proteomic profiles. Our framework enables the analysis of standard bulk, time-series, and single-cell measurements and includes various state-of-the-art methods to identify potentially deregulated biological processes and to detect driving factors within those deregulated processes. We highlight the capabilities of our web service with an analysis of a single-cell COVID-19 data set that demonstrates its potential for uncovering complex molecular mechanisms.GeneTrail can be accessed freely and without login requirements at http://genetrail.bioinf.uni-sb.de.