BenHur-class: Class "BenHur", a class for estimating clusters in microarray...
In clusterStab: Compute cluster stability scores for microarray data

Description Objects from the Class Slots Methods Author(s) References

A specialized class representation used for estimating clusters in microarray data.

Objects are usually created by a call to benhur, although technically a new object can also be created by a call to new("BenHur",...). However, this second method is usually not worth the work required.

jaccards:: Object of class "list", containing the jaccard vectors; these indicate the proportion of pairwise similarity between clusters formed from subsets of the data.
size:: Object of class "vector", only used for plotting.
iterations:: Object of class "vector", containing the number of iterations. Defaults to 100.
freq:: Object of class "vector", containing the proportion of the data used for subsampling.

ecdf: signature(x = "BenHur"): Plot an empirical CDF. This can be used to help determine the number of clusters in the data. The most likely (e.g., most stable number) of clusters will have a CDF that is concentrated at or near one. See vignette for more information.
hist: signature(x = "BenHur"): Plot histograms for all clusters tested. The most likely (e.g., most stable number) of clusters will have a histogram in which the data are clustered at or near one. See vignette for more information.
show: signature(object = "BenHur"): Gives a nice summary.

James W. MacDonald <jmacdon@u.washington.edu>

A. Ben-Hur, A. Elisseeff and I. Guyon. A stability based method for discovering structure in clustered data. Pacific Symposium on Biocomputing, 2002. Smolkin, M. and Ghosh, D. (2003). Cluster stability scores for microarray data in cancer studies. BMC Bioinformatics 4, 36 - 42.

clusterStab documentation built on Nov. 8, 2020, 8:23 p.m.