breast {integrativeME}R Documentation

Breast cancer data, a subset data set from van de Vijver et al. (2002) study

Description

Clinical and a subset of gene expression data from the van de Vijver et al. (2002) study.

Usage

data(breast)

Format

A list containing the following components:

type
vector of lenth 256 indicating the class of the patients (0 = recurrence, 1 = no recurrence).
cont
data matrix with 256 rows and 500 columns. The gene expression of 500 randomly sampled transcripts (for memory allocation reasons, see details).
indep
data matrix with 256 rows and 8 columns. The measurements of 8 clinical variables. The discrete data are suitable for a MElogreg or MEindep model in the mixture of experts methodology.
loc
data matrix with 256 rows and 7 columns. The measurements of 7 clinical variables. The discrete data are suitable for a MEloc model in the mixture of experts methodology.
loc.ind
indicates the location variable.

Details

The data set from van de Vijver et al. (2002) contains gene expression of tumors from 256 patients who were all treated by modified radical mastectomy or breast-conserving surgery. The authors also included some patients from the Van 't Veer et al. (2002) study and the censored patients were removed. The data were preprocessed and filtered to obtain 5,537 genes spotted on Agilent Hu25K microarrays. Eight prognostic factors were available in the clinical data and categorized as indicated by the authors.

For the location model, variables 'posnode' and 'chemotherapy' were merged into a single categorical variable (called the location variable).

Source

See website from the refered article. The original data with 5,537 transcripts can be downloaded as an .RData file from http://www.math.univ-toulouse.fr/~lecao/package.html

References

van de Vijver, M.J., He, Y.D., van' t Veer, L.J., Dai, H., Hart, A.A.M., Voskuil, D.W., Schreiber, G.J., Peterse, J.L., Roberts, C., Marton, M.J. and others (2002). A gene-expression signature as a predictor of survival in breast cancer. New England Journal of Medicine, 347, 25, 1999–2009.

Hunt, L. and Jorgensen, M. (1999). Mixture model clustering using the MULTIMIX program. Australian & New Zealand Journal of Statistics, 41, 2, 154–171.


[Package integrativeME version 1.1 Index]