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

Research output: Contribution to journalArticle

Abstract

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.

Details

Authors
Organisations
External organisations
  • Skåne University Hospital
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Cancer and Oncology
Original languageEnglish
Article numbere17911
JournalPLoS ONE
Volume6
Issue number3
Publication statusPublished - 2011
Publication categoryResearch
Peer-reviewedYes

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