impScores.plot: Importance score plot

In tgac-vumc/WECCA: Weighted clustering of array CGH data

Description

Plots importance scores against genomic order.

Usage

impScores.plot(impScores.table, yaxis.max = 10, lastchr = 22, color = "red")

Arguments

impScores.table	Table containing region annotation information and importance scores as returned by the function impScores.sc or impScores.hc.
yaxis.max	Maximum importance score to be plotted.
lastchr	Integer corresponding to chromosome number. This is the last chromosome whose importance scores are included in the plot.
color	Color of line connecting importance scores.

Author(s)

Wessel N. van Wieringen: [e-mail]

Examples

# generate object of class
data(WiltingCalled)

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

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

# generate a heatmap of the found clustering
WECCA.heatmap(WiltingRegioned, dendrogram)

# specify the number of clusters to be extracted from the dendrogram
nclusters <- 2
table.clusters.samples <- sample.cluster.table(WiltingRegioned, dendrogram, nclusters)

# calculate importance scores for each feature
impScores.table <- impScores.sc(WiltingRegioned, dendrogram, nclusters)

# plot importance scores
impScores.plot(impScores.table, yaxis.max=10, lastchr=22, color="red")

tgac-vumc/WECCA documentation built on May 31, 2019, 9 a.m.