Survival Online: A web-based service for the analysis of correlations between gene expression and clinical and follow-up data

Luca Corradi, Valentina Mirisola, Ivan Porro, Livia Torterolo, Marco Fato, Paolo Romano, Ulrich Pfeffer

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression data and clinico-pathological data through a combination of available and newly developed processing tools. Results: We developed Survival Online (available at http://ada.dist.unige.it:8080/enginframe/bioinf/bioinf.xml), a Web-based system that allows for the analysis of Affymetrix GeneChip microarrays by using a parallel version of dChip. The user is first enabled to select pre-loaded datasets or single samples thereof, as well as single genes or lists of genes. Expression values of selected genes are then correlated with sample annotation data by uni- or multi-variate Cox regression and survival analyses. The system was tested using publicly available breast cancer datasets and GO (Gene Ontology) derived gene lists or single genes for survival analyses. Conclusion: The system can be used by bio-medical researchers without specific computation skills to validate potential biomarkers or multi-gene classifiers. The design of the service, the parallelization of pre-processing tasks and the implementation on an HPC (High Performance Computing) environment make this system a useful tool for validation on several independent datasets.

Original languageEnglish
Article number1471
JournalBMC Bioinformatics
Volume10
Issue numberSUPPL. 12
Publication statusPublished - Oct 15 2009

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Structural Biology
  • Applied Mathematics

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