pathwayPlot: Plot of the pathyway topology as reconstructed from from DNA...
In sigaR: Statistics for Integrative Genomics Analyses in R

Description Usage Arguments Author(s) References See Also Examples

Plotting the topology of a pathway's regulatory network as reconstructed from from DNA copy number and gene expression data by the pathway1sample-function.

1 2	pathwayPlot(pFit, directed = TRUE, tWidth = 1, cWidth = 1, geWidth=10, cnWidth=10, circleDist = 1.5, gNames = NULL, main = "", remove = FALSE)

`pFit`	Object of class `pathwayFit` as returned by the function `pathway1sample`.
`directed`	A `logical` indicating whether to plot directed or undirected trans-effects.
`tWidth`	A `numeric` that scales the width of the trans-effect edges.
`cWidth`	A `numeric` that scales the width of the cis-effect edges.
`geWidth`	A `numeric` that scales the width of the gene expression nodes.
`cnWidth`	A `numeric` that scales the width of the DNA copy number nodes.
`circleDist`	A `numeric` that scales the inner and outer circle.
`gNames`	A `character` containing the gene names to written inside the nodes.
`main`	The `character` to be plotted as plot title.
`remove`	A `logical` indicating whether to remove genes without trans-effects.

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

Van Wieringen, W.N., Van de Wiel, M.A. (2012), "Modeling the cis- and trans-effect of DNA copy number aberrations on gene expression levels in a pathway", submitted for publication.

See also pathway1sample.

# set number of genes (p) and samples (n)
p <- 10
n <- 1000

# sample cis-effects
beta <- abs(rnorm(p))

# sample trans-effects
Theta <- matrix(sample(c(-1,1), p^2, replace=TRUE, prob=c(0.2, 0.8)), ncol=p) * 
	matrix(runif(p^2), ncol=p) / 4
diag(Theta) <- 1

# sample error variances
Sigma <- diag(rchisq(p, df=1)/5 + 0.5)

# sample DNA copy number data
X <- matrix(runif(n*p, min=-2, max=2), ncol=p)

# sample gene expression data
Y <- t(apply(X, 1, function(Y, beta){ Y * beta }, beta=beta)) %*% t(solve(Theta)) + 
	rmvnorm(n, sigma=solve(Theta) %*% Sigma %*% t(solve(Theta)))

# fit model
pFit <- pathway1sample(Y, X, lambda1=500)

# plot pathway topology
pathwayPlot(pFit, tWidth=5, cWidth=5)

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