R: NCI-60 cancer cell panel

nci60 {robustHD} | R Documentation

## 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)

[Package robustHD version 0.7.2 Index]