qpcR (version 1.1-8)

ratioplot: Plot method for data of class 'ratiocalc' which displays barplots of ratios with error bars

Description

A plot method in which data obtained from ratiocalc is displayed as a barplot or hanging barplot. Error bars can be added to the bars that had been calculated by any of the four different error values of propagate, i.e. propagated/Monte Carlo propagated/evaluated/Monte Carlo evaluated errors. Either significance codes or values from the t-tests can be added to the bars.

Usage

ratioplot(data, errbar = c("prop", "propSim", "eval", "evalSim", "none"), 
	  sem = FALSE, order = NA, y.fac = 1.5, normcol = NA, errwid = NULL, 
	  type = c("bar", "hbar"), plot.t = c("none", "stars", "values"), 
	  offset = 1, ...)

Arguments

data

data of class 'ratiocalc'.

errbar

type of error that is used in displaying the error bars. See 'Details'.

sem

logical. Should the standard error of the mean (s.d./sqrt(n)) be displayed?

order

a numeric vector defining subsets or reordering of the plotted bars.

y.fac

multiplication factor for the y-axis extension, can be tweaked for a more appealing output.

normcol

column number that all other data should be normalized against. See 'Details'.

errwid

The width of the error bars. If NULL (default), calculated from the width of the bars.

type

the plot type. See 'Details'.

plot.t

how to display the results from the t-tests. Either significance codes (i.e. < 0.01 => "**") or the p-values.

offset

distance of plot.t from the end of the bars. For tweaking.

...

other parameters to be passed to barplot or arrows.

Value

• A barplot with error bars displaying the ratios obtained from ratiocalc.

Details

Ratios are displayed from all permutations/combinations of sample/replicate sample PCR runs, as described in ratiocalc. The data can also be normalized against one of the runs, in which the 'control' data is normalized to 1 and all other data and their errors accordingly. The following error types can be displayed: prop the propagated error (standard deviation); propSim the propagated error averaged from Monte Carlo simulation; eval the (unpropagated) error (standard deviation) resulting from averaging the expression evaluation; evalSim the (unpropagated) error (standard deviation) from the evaluated expressions of the Monte Carlo simulation. If type = "bar", a normal error bar plot is displayed. If type = "hbar", ratios < 1 are displayed as hanging bars with (-1/value). The latter is more appealing and visually discriminates the up-/down-regulated samples.

Examples

## quick (but not dirty!) analysis of qPCR data!
## normal bar plot with standard error of mean
## and t-test on crossing points
DAT <- modlist(reps, 2:9, fct = l5())
GROUP <- c(1, 1, 2, 2, 3, 3, 4, 4)
res <-  ratiocalc(DAT, group = GROUP, ttest = "cp")
ratioplot(res, cex.names = 0.3, sem = TRUE, plot.t = "values")

## hanging bar plot with standard deviation
## and significance codes
ratioplot(res, cex.names = 0.3, type = "hbar", plot.t = "stars")

## same using the 'unpropagated' error and
## different y-scale
## (from averaged expression evaluations)
ratioplot(res, cex.names = 0.3, type = "hbar", 
	  errbar = "eval", ylim = c(-20, 59))