splinePlot: Plot spline regression curves of time-course data

Description

Function visualises time dependent behaviour of genes in two compared groups. The natural cubic spline regression curves fitted to discrete, time dependent expression data are plotted. One plot shows two curves - representing the reference group and the compared group, respectively. See also splineDiffExprs function.

Usage

splinePlot(eSetObject, df, reference, toPlot="all")

Arguments

eSetObject

ExpressionSet object of class ExpressionSet containing log-ratios or log-values of expression for a series of microarrays

number of degrees of freedom

reference

character defining which treatment group should be considered as reference

toPlot

vector of genes to plot; defalut is toPlot = "all"

Value

A .pdf file containing plots for chosen genes.

Details

The input eSetObject must be provided as an object of class ExpressionSet which contains SampleName, Time, Treatment and if applicable Replicates variables (columns) included in the phenotypic data of the eSetObject (pData(eSetObject)). Two types of Treatment defining two groups to compare have to be definied.

Replicates are not required. The time points for compared treatment groups should be identical.

User has to define number of degrees of freedom (df) for the spline regression model. Choosing effective degrees of freedom in range 3-5 is reasonable.

Genes to plot, given as a vector of characters, can be selected by the user. Provided names have to be a part of a row name vector of eSetObject (rownames(exprs(eSetObject))). If genes to plot are not definied, all genes are plotted.

Examples

Run this code

## load "eSetObject" object containing simulated time-course data
data(TCsimData)
pData(TCsimData)

## define function parameters 
df <- 3
reference <- "T1"
toPlot <- rownames(TCsimData)[1:10]

splinePlot(eSetObject = TCsimData, df, reference, toPlot)