R: Sample Test Data for the Iterative BMA Algorithm for Survival...
testData
R Documentation
Sample Test Data for the Iterative BMA Algorithm for Survival Analysis
Description
This is an adapted diffuse large B-cell lymphoma (DLBCL) dataset from
Rosenwald et al. (2002). This data matrix consists of the expression
levels from 36 DLBCL samples (rows), and 100 top univariate genes
(columns). This dataset is used as a sample test set in our examples.
Usage
data(trainData)
Format
The data matrix is called testData. Each entry
in the matrix represents the expression level of one gene from
a DLBCL sample.
Details
We started with the full expression data from Rosenwald et al. (2002),
which is available along with corresponding patient information at their
supplemental website http://llmpp.nih.gov/DLBCL/. We selected
a subset of the 80 test samples, and then performed Cox Proportional
Hazards Regression to obtain the 100 genes with the highest log likelihood.
The filtered dataset consists of 36 test samples, and it is available at
our website http://expression.washington.edu/ibmasurv/protected.
Rosenwald, A., Wright, G., Wing, C., Connors, J., Campo, E. et al. (2002).
The Use of Molecular Profiling to Predict Survival After Chemotherapy for Diffuse Large-B-Cell Lymphoma.
The New England Journal of Medicine, 346(25), 1937-1947.