mpmSpectral maps are special types of biplots with the area of the symbols
proportional to some measure, usually the row or column mean value and an
identification of row- and column-items. For large matrices, such as gene
expression data, where there is an abundance of rows, this can obscure the
plot. In this case, the argument label.tol can be used to select the
most informative rows, i.e. rows that are most distant from the center of
the plot. Only these row-items are then labeled and represented as circles
with their areas proportional to the marginal mean value. For the
column-items it can be useful to apply some grouping specified by
col.group. Examples of groupings are different pathologies, such as
specified in Golub.grp
# S3 method for mpm
plot(
x,
scale = c("singul", "eigen", "uvr", "uvc"),
dim = c(1, 2),
zoom = rep(1, 2),
show.row = c("all", "position"),
show.col = c("all", "position"),
col.group = rep(1, length(x$col.names)),
colors = c("orange1", "red", rainbow(length(unique(col.group)), start = 2/6, end =
4/6)),
col.areas = TRUE,
col.symbols = c(1, rep(2, length(unique(col.group)))),
sampleNames = TRUE,
rot = rep(-1, length(dim)),
labels = NULL,
label.tol = 1,
label.col.tol = 1,
lab.size = 0.725,
col.size = 10,
row.size = 10,
do.smoothScatter = FALSE,
do.plot = TRUE,
...
)object of class mpm a result of a call to mpm.
optional character string specifying the type of factor scaling of the biplot. This can be either "singul" (singular value scaling), "eigen" (eigenvalue scaling), "uvr" (unit row-variance scaling), "uvc" (unit column-variance scaling). The latter is of particular value when analyzing large matrices, such as gene expression data. Singular value scaling "singul" is customary in spectral map analysis. Defaults to "singul".
optional principal factors that are plotted along the horizontal
and vertical axis. Defaults to c(1,2).
optional zoom factor for row and column items. Defaults to
c(1,1).
optional character string indicating whether all rows ("all") are to be plotted or just the positioned rows "position".
optional character string indicating whether all columns ("all") are to be plotted or just the positioned columns "position".
optional vector (character or numeric) indicating the
different groupings of the columns, e.g. Golub.grp. Defaults to 1.
vector specifying the colors for the annotation of the plot; the first two elements concern the rows; the third till the last element concern the columns; the first element will be used to color the unlabeled rows; the second element for the labeled rows and the remaining elements to give different colors to different groups of columns.
logical value indicating whether columns should be plotted
as squares with areas proportional to their marginal mean and colors
representing the different groups (TRUE), or with symbols
representing the groupings and identical size (FALSE). Defaults to
TRUE.
vector of symbols when col.areas=FALSE corresponds
to the pch argument of the function plot.
Either a logical vector of length one or a character
vector of length equal to the number of samples in the dataset. If a
logical is provided, sample names will be displayed on the plot
(TRUE; default) or not (FALSE); if a character vector is
provided, the names provided will be used to label the samples instead of
the default column names.
rotation of plot. Defaults to c(-1,-1).
character vector to be used for labeling points on the graph;
if NULL, the row names of x are used instead
numerical value specifying either the percentile
(label.tol<=1) of rows or the number of rows (label.tol>1)
most distant from the plot-center (0,0) that are labeled and are plotted
as circles with area proportional to the marginal means of the original
data.
numerical value specifying either the percentile
(label.col.tol<=1) of columns or the number of columns (label.col.tol>1)
most distant from the plot-center (0,0) that are labeled and are plotted
as circles with area proportional to the marginal means of the original
data.
size of identifying labels for row- and column-items as
cex parameter of the text function
size in mm of the column symbols
size in mm of the row symbols
use smoothScatter or not instead of plotting individual points
produce a plot or not
further arguments to eqscaleplot which draws the canvas
for the plot; useful for adding a main or a custom sub
An object of class plot.mpm that has the following
components:
a data frame with the X and Y coordinates of the
rows and an indication Select of whether the row was selected
according to label.tol
a data frame with the X and Y coordinates of the columns
Wouters, L., Goehlmann, H., Bijnens, L., Kass, S.U., Molenberghs, G., Lewi, P.J. (2003). Graphical exploration of gene expression data: a comparative study of three multivariate methods. Biometrics 59, 1131-1140.
# NOT RUN {
# Weighted spectral map analysis
data(Golub) # Gene expression data of leukemia patients
data(Golub.grp) # Pathological classes coded as 1, 2, 3
r.sma <- mpm(Golub[,1:39], row.weight = "mean", col.weight = "mean")
# Spectral map biplot with result
r <- plot(r.sma, label.tol = 20, scale = "uvc",
col.group = (Golub.grp)[1:38], zoom = c(1,1.2), col.size = 5)
Golub[r$Rows$Select, 1] # 20 most extreme genes
# }
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