eigengenes33 {Pigengene}R Documentation

Eigengenes of 33 modules

Description

This list contains partial eigengenes computed from AML and MDS gene expression profiles provided by Mills et al. These data are included to illustrate how to use Pigengene-package and also to facilitate reproducing the results presented in the corresponding paper.

Usage

data(eigengenes33)

Format

A list

Details

The top 9166 differentially expressed genes were identified and their expressions in AML were used for identifying 33 modules. The first column, ME0, corresponds to module 0 (outliers) and is usually ignored. The eigengene for each module was obtained using compute.pigengene function. Oversampling was performed with amplification=5 to adjust for unbalanced sample-size.

Value

It is a list of 3 objects:

aml A 202 by 34 matrix. Each column reports the values of a module eigengene for AML cases.

mds A 164 by 34 matrix for MDS cases with columns similar to aml.

modules A numeric vector of length 9166 labeling members of each module. Named by Entrez ID.

Source

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15061

References

Mills, Ken I., et al. (2009). Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome. Blood 114.5: 1063-1072.

See Also

Pigengene-package, compute.pigengene, aml, mds, learn.bn

Examples

library(pheatmap)
data(eigengenes33)
pheatmap(eigengenes33$aml,show_rownames=FALSE)
## See Pigengene::learn.bn() documentation for more examples.

[Package Pigengene version 1.18.10 Index]