Change search
ReferencesLink to record
Permanent link

Direct link
Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier
Lund University.
2010 (English)In: BMC Cancer, ISSN 1471-2407, Vol. 10, 532- p.Article in journal (Refereed) Published
Abstract [en]

Background: Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms.Results: The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies.Conclusions: We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at

Place, publisher, year, edition, pages
2010. Vol. 10, 532- p.
Keyword [en]
Microarrays, Diagnosis, Survival
National Category
Medical and Health Sciences
URN: urn:nbn:se:kth:diva-61154DOI: 10.1186/1471-2407-10-532ISI: 000283654600002PubMedID: 20925936OAI: diva2:478645
QC 20120118Available from: 2012-01-16 Created: 2012-01-16 Last updated: 2012-01-18Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Rydén, Tobias
In the same journal
BMC Cancer
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 15 hits
ReferencesLink to record
Permanent link

Direct link