WECCAsc: Weighted clustering of array CGH data (soft calls).
In tgac-vumc/WECCA: Weighted clustering of array CGH data

Description Usage Arguments Details Value Author(s) References See Also Examples

Weighted distance matrix calculation, followed by dendrogram construction for regioned call probability array CGH data.

1	WECCAsc(cghdata.regioned, dist.measure = "KLdiv", linkage = "ward", weight.type = "all.equal")

`cghdata.regioned`	A `list`-object as returned by the function `regioning.sc`.
`dist.measure`	The distance measure to be used. This is either `"KLdiv"` (the symmetric Kullback-Leibler divergence) or `"ordinal"` (distance between the cumulative call probability distributions).
`linkage`	The linkage method to be used, like `"single"`, `"average"`, `"complete"`, `"ward"`.
`weight.type`	Region weighting to be used in the calculation of the distance, either `"all.equal"` or `"heterogeneity"`.

The distance between the call probability profiles of all sample pairs are calculated using special distance measures suitable for this data type. The distance between the call probability signature of two regions is either defined as the symmetric Kullback-Leibler divergence or as the absolute distance between their cumulative call probability distributions. The distance between two call probability profiles is defined as a weighted average of the distances between individual regions. Region weighing currently implemented: no-weighing (all regions contribute equally to the overall distance), or heterogeneity weighing (weights are proportional to their Shannon's entropy). Once the distance matrix has been calculated, this is submitted to the hclust function, which clusters the samples hierarchically, returning a dendrogram.

An object of class hclust which describes the tree produced by the clustering process. See hclust for a list of its components.

Wessel N. van Wieringen: w.vanwieringen@vumc.nl

Van Wieringen, W.N., Van de Wiel, M.A., Ylstra, B. (2008), "Weighted clustering of called aCGH data", Biostatistics, 9(3), 484-500.

Smeets, S.J., Brakenhoff, R.H., Ylstra, B., Van Wieringen, W.N., Van de Wiel, M.A., Leemans, C.R., Braakhuis, B.J.M. (2009), "Genetic classification of oral and oropharyngeal carcinomas identifies subgroups with a different prognosis", Cellular Oncology, 39, 291–300.

dist, hclust, KLdiv, regioning

# generate object of cghCall-class
data(WiltingCalled)

# make region data (soft and hard calls)
WiltingRegioned <- regioning(WiltingCalled)

# clustering with soft.calls
dendrogram <- WECCAsc(WiltingRegioned)