maSigPro (version 1.44.0)

PlotProfiles: Function for visualization of gene expression profiles

Description

PlotProfiles displays the expression profiles of a group of genes.

Usage

PlotProfiles(data, cond, main = NULL, cex.xaxis = 0.5, ylim = NULL,  repvect, sub = NULL, color.mode = "rainbow")

Arguments

data

a matrix containing the gene expression data

cond

vector for x axis labeling, typically array names

main

plot main title

cex.xaxis

graphical parameter maginfication to be used for x axis in plotting functions

ylim

index vector indicating experimental replicates

repvect

index vector indicating experimental replicates

sub

plot subtitle

color.mode

color scale for plotting profiles. Can be either "rainblow" or "gray"

Value

Details

The repvect argument is used to indicate with vertical lines groups of replicated arrays.

References

Conesa, A., Nueda M.J., Alberto Ferrer, A., Talon, T. 2005. maSigPro: a Method to Identify Significant Differential Expression Profiles in Time-Course Microarray Experiments.

See Also

PlotGroups

Examples

#### GENERATE TIME COURSE DATA
## generate n random gene expression profiles of a data set with 
## one control plus 3 treatments, 3 time points and r replicates per time point.

tc.GENE <- function(n, r,
             var11 = 0.01, var12 = 0.01,var13 = 0.01,
             var21 = 0.01, var22 = 0.01, var23 =0.01,
             var31 = 0.01, var32 = 0.01, var33 = 0.01,
             var41 = 0.01, var42 = 0.01, var43 = 0.01,
             a1 = 0, a2 = 0, a3 = 0, a4 = 0,
             b1 = 0, b2 = 0, b3 = 0, b4 = 0,
             c1 = 0, c2 = 0, c3 = 0, c4 = 0)
{

  tc.dat <- NULL
  for (i in 1:n) {
    Ctl <- c(rnorm(r, a1, var11), rnorm(r, b1, var12), rnorm(r, c1, var13))  # Ctl group
    Tr1 <- c(rnorm(r, a2, var21), rnorm(r, b2, var22), rnorm(r, c2, var23))  # Tr1 group
    Tr2 <- c(rnorm(r, a3, var31), rnorm(r, b3, var32), rnorm(r, c3, var33))  # Tr2 group
    Tr3 <- c(rnorm(r, a4, var41), rnorm(r, b4, var42), rnorm(r, c4, var43))  # Tr3 group
    gene <- c(Ctl, Tr1, Tr2, Tr3)
    tc.dat <- rbind(tc.dat, gene)
  }
  tc.dat
}

## create 10 genes with profile differences between Ctl, Tr2, and Tr3 groups
tc.DATA <- tc.GENE(n = 10,r = 3, b3 = 0.8, c3 = -1, a4 = -0.1, b4 = -0.8, c4 = -1.2)
rownames(tc.DATA) <- paste("gene", c(1:10), sep = "")
colnames(tc.DATA) <- paste("Array", c(1:36), sep = "")

PlotProfiles (tc.DATA, cond = colnames(tc.DATA), main = "Time Course", 
              repvect = rep(c(1:12), each = 3))