"Block", "Row" and "Column" information of an
EList or EListRaw object to resemble the original positions on the
array(s). The resulting plot is similar to the original scan image of the
considered array(s). Thus, this function is a visualization tool that can be
used to visualize protein microarrays for which the original scan image is not
available. Visual inspection of the spatial expression pattern can then identify
possible local tendencies and strong spatial biases. Moreover, the array can be
inspected at all stages of the preprocessing workflow in order to check the
impact of the particular methods that have been applied.
plotArray(elist=NULL, idx=NULL, data.type="fg", log=NULL, normalized=NULL, aggregation=NULL, colpal="heat.colors", graphics.device="tiff", output.path=NULL)EList or EListRaw object (mandatory)."all" indicating
the column indices of the sample(s) for drawing the plot(s) (mandatory)."fg") or
background ("bg") data should be plotted. The default is "fg"
(optional).elist was normalized
(mandatory).elist has been aggregated and, if this is the case, which method has
been used by the function loadGPR(). Possible values are
"min", "mean" and "none"(mandatory)."heat.colors" (optional).output.path. Accepted values are "tiff" and "png".
The default is "tiff" (optional).gplots
function heatmap.2() for visual quality control. The data obtained
from an EList or EListRaw object is re-ordered and represented
in the same way the spots are ordered on the actual microarray. Consequently,
the resulting plot is similar to the original scan image of the considered
array. This allows for visual control and assessment of possible patterns in
spatial distribution.Mandatory arguments are elist, idx, log, normalized
and aggregation. While elist specifies the EList
or EListRaw object to be used, idx designates the array
column index in elist to plot a single array from the EList
object. Alternatively, a vector (e.g., 1:5) or the string "all"
can be designated to include multiple, respectively, all arrays that were
imported.
Furthermore, data.type allows for plotting of "fg", foreground
data (i.e., elist$E and elist$C), which is the default or
"bg", background data (i.e., elist$Eb and elist$Cb).
The normalization approaches of PAA which comprise also data logarithmization
do not include control data. With normalized=TRUE it is indicated that
the input data was normalized, so the control data will be logarithmized (log2)
before plotting as well. However, since the complete data (foreground and
background values of protein features and control spots) can be logarithmized
regardless of normalization the argument log states whether the
designated data is already logarithmized (note: log2 scale is always expected).
The parameter aggregation indicates whether the protein microarray
data has been aggregated by loadGPR() and, if so, which method has been
used.
Moreover, the parameter colpal defines the color palette that will
be used for the plot. Some exemplary values are "heat.colors" (default),
"terrain.colors", "topo.colors", "greenred" and
"bluered".
Finally, the output path optionally can be specified with the argument
output.path to save the plot(s). Then, one or more tiff or png file(s)
containing the corresponding plot(s) are saved into the subfolder "array_plots".
gplots by Gregory R. Warnes et al. can be downloaded from
CRAN (http://CRAN.R-project.org/package=gplots). Gregory R. Warnes, Ben Bolker, Lodewijk Bonebakker, Robert Gentleman, Wolfgang Huber, Andy Liaw, Thomas Lumley, Martin Maechler, Arni Magnusson, Steffen Moeller, Marc Schwartz and Bill Venables (2015). gplots: Various R Programming Tools for Plotting Data. R package version 2.17.0. http://CRAN.R-project.org/package=gplots
cwd <- system.file(package="PAA")
load(paste(cwd, "/extdata/BadData.RData", sep=""))
plotArray(elist=bad.elist, idx=1, data.type="bg", log=FALSE, normalized=FALSE,
aggregation="none")
Run the code above in your browser using DataLab