PlotProfiles: Function for visualization of gene expression profiles

In mjnueda/maSigPro: Significant Gene Expression Profile Differences in Time Course Gene Expression Data

Description

PlotProfiles displays the expression profiles of a group of genes.

Usage

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

Arguments

data	a matrix containing the gene expression data
cond	vector for x axis labeling, typically array names
cex.axis	graphical parameter maginfication to be used for x axis in plotting functions
ylim	index vector indicating experimental replicates
repvect	index vector indicating experimental replicates
main	plot main title
sub	plot subtitle
color.mode	color scale for plotting profiles. Can be either "rainblow" or "gray"
item	Name of the analysed items to show

Details

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

Value

Plot of experiment-wide gene expression profiles.

Author(s)

Ana Conesa and Maria Jose Nueda, [e-mail]

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))

mjnueda/maSigPro documentation built on Dec. 11, 2020, 12:21 a.m.