opm(According section in the tutorial: 3.7. Plotting functions for raw data)
Now we load and attach the opm functions. Note that if a package such as
opm has already been loaded, the library command does nothing. It thus
can be called at any time.
library(pkgutils)
library(opm)
BEGIN code we only need here for users which have no PM data of their own
# Here we check whether a data object `x` has been created by reading PM data
# files. If otherwise, we assign an existing example object to it.
#
if (!exists("x") || length(x) == 0) {
warning("data object 'x' from part 1 is missing or empty, using 'vaas_4'")
x <- as(vaas_4, "MOPMX") # this example object comes with the opm package
metadata(x) <- "ID" # set unique IDs
}
END code we only need here for users which have no PM data of their own
Now we create some plots, first without metadata. We can indeed plot our PM plates without considering metadata, but this apparently yields not particularly informative plots.
These functions create one plot per plate type. This avoids comparing apples with oranges. Wells from distinct plate types cannot can sensibly be compared in most kinds of single plots.
print(xy_plot(x)) # so-called x-y plot
## $`Gen III`
print(level_plot(x)) # so-called level plot
## $`Gen III`
A command to show the dimensions of the data for the first plate type:
dim(x[[1]])
## [1] 4 384 96
This yields:
The first 8 wells of the first plate type in x if it has > 1 plate:
print(xy_plot(x[[1]][, , 1:8]))
The first 8 wells of the first plate type in x if it has 1 plate:
print(xy_plot(x[[1]][, 1:8]))
The first 50 time points of the first plate type in x if it has > 1 plate:
print(xy_plot(x[[1]][, 1:50]))
The first 50 time points of the first plate type in x if it has > 1 plate:
print(xy_plot(x[[1]][1:50]))
You can create subsets at any time, but what is allowed depends on the dimensions of the data. If you select beyond the real range, an error results.
A way more interesting approach is to make use of the stored metadata, if any.
You could check whether 'Strain' occurs in the metadata keys of all of the
plates as follows. (Otherwise the plotting functions would crash if 'Strain'
is within the include argument, as below.)
if (all(unlist("Strain" %k% x))) {
## the code would come here
}
Here the proper plotting code is as in 3.3 but note the argument include.
print(xy_plot(x, include = "Strain"))
## $`Gen III`
Next we make use of two metadata entries.
print(level_plot(x, include = list("Strain", "ID")))
## $`Gen III`
Please watch the generated plots carefully and determine how the selected metadata entry has been used. If you have other metadata entries in your own data, use those.
Now proceed with part 4.