eigengenes33 {Pigengene} | R Documentation |
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.
data(eigengenes33)
A list
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.
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.
http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15061
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.
Pigengene-package
, compute.pigengene
,
aml
, mds
,
learn.bn
library(pheatmap) data(eigengenes33) pheatmap(eigengenes33$aml,show_rownames=FALSE) ## See Pigengene::learn.bn() documentation for more examples.