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CALIB (version 1.38.0)

plotNormalizedData: plot estimated absolute levels of two conditions

Description

plot estimated absolute levels of any two user-specified conditions. The values in the plot are in log scale.

Usage

plotNormalizedData(data, condition = c(1, 2), xlab = NULL, ylab = NULL, main = NULL,xlim = NULL, ylim = NULL, pch = 19, cex = 0.2,col = "black", diag=TRUE, diagcol="blue", diaglwd=1.5, ...)

Arguments

data
matrix containing estimated absolute levels. columns are conditons and rows are genes.
condition
integer vector giving the two conditions to be plotted.
xlab
a title for the x axis.
ylab
a title for the y axis.
main
an overall title for the plot.
xlim
the x limits (min,max) of the plot.
ylim
the y limits of the plot.
pch
an integer code for one of a set of plotting characters or symbols for the spike data set. Default is 19.
cex
a numerical value giving the amount by which points should be scaled relative to the default. Default is 0.2.
col
the color of the points. Default is black.
diag
a logical value. Add diagonal on the plot if it is TRUE. Default is TRUE.
diagcol
the color of the diagonal. Default is blue.
diaglwd
the width of the diagonal. Default is 1.5.
...
other graphical parameters can be used in function plot.

Value

A plot is created on the current graphics device.

Details

The function polts estimated absolute expression levels of two conditions. It accepts expression levels from the argument 'data', which should have the same data format as the output value of the function normalizeData.

The two conditions to be plotted should be specified by the argument condition. The condition should be a numeric vector with length two and it should be subset of condition vector of the design matrix. see function NormalizeData.

see other graphic functions for the other arguments.

Examples

Run this code
# load data: normalized data
data(normdata)
	
# specify the two conditions to be plotted.
cond <- c(1,2)
	
# use the default values for other parameters.
plotNormalizedData(normdata,condition = cond)

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