NCI-60 cancer cell panel

Description

The data set is a pre-processed version of the NCI-60 cancer cell panel as used in Alfons, Croux & Gelper (2013). One observation was removed since all values in the gene expression data were missing.

Usage

data("nci60")

Format

Protein and gene expression data on 59 observations are stored in two separate matrices:

protein

a matrix containing protein expressions based on antibodies (162 variables), acquired via reverse-phase protein lysate arrays and log2 transformed.

gene

a matrix containing gene expression data (22283 variables), obtained with an Affymetrix HG-U133A chip and normalized with the GCRMA method.

Source

The original data were downloaded from https://discover.nci.nih.gov/cellminer/ on 2012-01-27. They can be obtained from https://github.com/aalfons/nci60, together with our script for pre-processing.

References

Reinhold, W.C., Sunshine, M., Liu, H., Varma, S., Kohn, K.W., Morris, J., Doroshow, J. and Pommier, Y. (2012) CellMiner: A Web-Based Suite of Genomic and Pharmacologic Tools to Explore Transcript and Drug Patterns in the NCI-60 Cell Line Set. Cancer Research, 72(14), 3499–3511.

Alfons, A., Croux, C. and Gelper, S. (2013) Sparse least trimmed squares regression for analyzing high-dimensional large data sets. The Annals of Applied Statistics, 7(1), 226–248.

Examples

## Not run: 

# load data
data("nci60")
# define response variable
y <- protein[, 92]
# screen most correlated predictor variables
correlations <- apply(gene, 2, corHuber, y)
keep <- partialOrder(abs(correlations), 100, decreasing = TRUE)
X <- gene[, keep]

## End(Not run)