Menu

Javascript is not activated in your browser. This website needs javascript activated to work properly.
You are here

GOBO: Gene Expression-Based Outcome for Breast Cancer Online.

Author:
  • Markus Ringnér
  • Erik Fredlund
  • Jari Häkkinen
  • Åke Borg
  • Johan Staaf
Publishing year: 2011
Language: English
Publication/Series: PLoS ONE
Volume: 6
Issue: 3
Document type: Journal article
Publisher: Public Library of Science

Abstract english

Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo), allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1) rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2) identification of co-expressed genes for creation of potential metagenes, 3) association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Keywords

  • Cancer and Oncology

Other

Published
  • CREATE Health
  • ISSN: 1932-6203
Markus Ringnér
E-mail: markus [dot] ringner [at] biol [dot] lu [dot] se

Research engineer

Molecular Cell Biology

B-A317

Sölvegatan 35, Lund

4