data: Data sets for the clusterCons package

In clusterCons: Consensus Clustering using Multiple Algorithms and Parameters

Data sets for the clusterCons package

Description

These data sets are used by the examples in the package function descriptions and allow the user to explore the functionality of the package

Usage

data(golub);
data(sim_class);
data(sim_profile);
data(testcmr);

Format

golub : data.frame of gene expression values for 999 genes for 38 leukemia patients (1-27) ALL and (28-38) AML. sim_class : data.frame of 200 simulated gene expression values for 30 conditions where there are 4 discrete classes of expression profile, for testing clustering with the transposed data (clustering by column). sim_profile : data.frame of 120 simulated gene expression values for 4 conditions where there are 4 discrete classes of expression profile, for testing general clustering (clustering by row). testcmr : list of consensus and merge matrix results from a cluscomp run (see consmatrix-class and mergematrix-class).

Author(s)

Dr. T. Ian Simpson [e-mail]

References

Merged consensus clustering to assess and improve class discovery with microarray data. Simpson TI, Armstrong JD and Jarman AP. BMC Bioinformatics 2010, 11:590.

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Golub, TR and Slonim, DK and Tamayo, P and Huard, C and Gaasenbeek, M and Mesirov, JP and Coller, H and Loh, ML and Downing, JR and Caligiuri, MA and Bloomfield, CD and Lander, ES. Science 1999, 286:531-537

Examples

#cluster by class
data(sim_class);
cutree(agnes(t(sim_class)),4);

#cluster by profile
data(sim_profile);
cutree(agnes(sim_profile),4);

clusterCons documentation built on March 18, 2022, 5:16 p.m.