GeneTrail—advanced gene set enrichment analysis

By Christina Backes, Andreas Keller, Jan Küntzer, B. Kneissl, N. Comtesse, Yasser A. Elnakady, R. Müller, E. Meese, Hans-Peter Lenhof. Nucleic Acids Res., 2007

369 citations recorded by the source corpus.

We present a comprehensive and efficient gene set analysis tool, called ‘GeneTrail’ that offers a rich functionality and is easy to use. Our web-based application facilitates the statistical evaluation of high-throughput genomic or proteomic data sets with respect to enrichment of functional categories. GeneTrail covers a wide variety of biological categories and pathways, among others KEGG, TRANSPATH, TRANSFAC, and GO. Our web server provides two common statistical approaches, ‘Over-Representation Analysis’ (ORA) comparing a reference set of genes to a test set, and ‘Gene Set Enrichment Analysis’ (GSEA) scoring sorted lists of genes. Besides other newly developed features, GeneTrail's statistics module includes a novel dynamic-programming algorithm that improves the P-value computation of GSEA methods considerably. GeneTrail is freely accessible at http://genetrail.bioinf.uni-sb.de

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5941eef480744e281b3fb48dfe640af215bee586

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

  1. Danzhi Huang
  2. Richard A. Lempicki
  3. Brad T. Sherman
  4. Maria D. Paraskevopoulou
  5. Artemis G. Hatzigeorgiou
  6. Martin Reczko
  7. Theodore Dalamagas
  8. Ioannis S. Vlachos

Citations in the corpus