checks: Functions to check the integrity of various objects

In clusterCons: Consensus Clustering using Multiple Algorithms and Parameters

Functions to check the integrity of various objects

Description

These methods are mainly internal although the user may like to check their original data using data_check before they perform consensus clustering experiments.

Usage

data_check(x)
validConsMatrixObject(object)
validMemRobListObject(object)
validMemRobMatrixObject(object)
validMergeMatrixObject(object)
validAUCObject(object)
validDkObject(object)

Arguments

x	The data.frame object to be checked prior to using with the cluscomp function.
object	The object to be checked with the suitable function by type. These are used internally by several of the functions in the package.

Value

returns TRUE if check is passed or an error message if it is not

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.

Examples

#load data
data(sim_profile);

#check if this can be used by cluscomp
data_check(sim_profile);

#perform a clusomp run
cmr <- cluscomp(sim_profile,clmin=2,clmax=2,rep=10);

#check one of the consensus matrices
validConsMatrixObject(cmr$e1_kmeans_k2)

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