plotIndiv: Plot of Individuals (Experimental Units)
In mixOmicsTeam/mixOmics: Omics Data Integration Project
plotIndiv R Documentation
Plot of Individuals (Experimental Units)
Description
This function provides scatter plots for individuals (experimental units)
representation in (sparse)(I)PCA, (regularized)CCA, (sparse)PLS(DA) and
(sparse)(R)GCCA(DA).
Usage
plotIndiv(object, ...)
## S3 method for class 'mint.pls'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'mint.spls'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'mint.plsda'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'mint.splsda'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'pca'
plotIndiv(
object,
comp = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
...
)
## S3 method for class 'mixo_pls'
plotIndiv(
object,
comp = NULL,
rep.space = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'sgcca'
plotIndiv(
object,
comp = NULL,
blocks = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
...
)
## S3 method for class 'rgcca'
plotIndiv(
object,
comp = NULL,
blocks = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
...
)
Arguments
object
object of class inherited from any mixOmics: PLS,
sPLS, PLS-DA, SPLS-DA, rCC, PCA, sPCA, IPCA, sIPCA, rGCCA, sGCCA, sGCCDA
...
Optional arguments or type par can be added with style =
'graphics'
comp
integer vector of length two (or three to 3d). The components
that will be used on the horizontal and the vertical axis respectively to
project the individuals.
study
Indicates which study-specific outputs to plot. A character
vector containing some levels of object$study, "all.partial" to plot
all studies or "global" is expected. Default to "global".
rep.space
For objects of class "pca", "plsda", "plsda" default
is "X-variate". For the objects of class "pls", "rcc" default
is a panel plot representing each data subspace. For objects of class
"rgcca" and "sgcca", numerical value(s) indicating the block
data set to represent needs to be specified.
group
factor indicating the group membership for each sample, useful
for ellipse plots. Coded as default for the supervised methods PLS-DA,
SPLS-DA,sGCCDA, but needs to be input for the unsupervised methods
PCA, sPCA, IPCA, sIPCA, PLS, sPLS, rCC, rGCCA, sGCCA. Order of levels will reflect
order in legends and correspond to any set colours.
col.per.group
character (or symbol) color to be used when 'group' is
defined. Vector of the same length as the number of groups.
style
argument to be set to either 'graphics',
'lattice', 'ggplot2' or '3d' for a style of plotting.
Default set to 'ggplot2'. See details. 3d is not available for MINT
objects.
ellipse
Logical indicating if ellipse plots should be plotted. In the
non supervised objects PCA, sPCA, IPCA, sIPCA, PLS, sPLS, rCC, rGCCA,
sGCCA ellipse plot is only be plotted if the argument group is
provided. In the PLS-DA, SPLS-DA,sGCCDA supervised object, by default
the ellipse will be plotted accoding to the outcome Y.
ellipse.level
Numerical value indicating the confidence level of
ellipse being plotted when ellipse =TRUE (i.e. the size of the
ellipse). The default is set to 0.95, for a 95% region.
centroid
Logical indicating whether centroid points should be
plotted. In the non supervised objects PCA, sPCA, IPCA, sIPCA, PLS,
sPLS, rCC, rGCCA, sGCCA the centroid will only be plotted if the argument
group is provided. The centroid will be calculated based on the group
categories. In the supervised objects PLS-DA, SPLS-DA,sGCCDA the
centroid will be calculated according to the outcome Y.
star
Logical indicating whether a star plot should be plotted, with
arrows starting from the centroid (see argument centroid, and ending
for each sample belonging to each group or outcome. In the non supervised
objects PCA, sPCA, IPCA, sIPCA, PLS, sPLS, rCC, rGCCA, sGCCA star
plot is only be plotted if the argument group is provided. In the
supervised objects PLS-DA, SPLS-DA,sGCCDA the star plot is plotted
according to the outcome Y.
title
set of characters indicating the title plot.
subtitle
subtitle for each plot, only used when several block
or study are plotted.
legend
Logical. Whether the legend should be added. Default is FALSE.
X.label
x axis titles.
Y.label
y axis titles.
abline
should the vertical and horizontal line through the center be
plotted? Default set to FALSE
xlim, ylim
numeric list of vectors of length 2 and length
=length(blocks), giving the x and y coordinates ranges.
col
character (or symbol) color to be used, possibly vector.
cex
numeric character (or symbol) expansion, possibly vector.
pch
plot character. A character string or a vector of single
characters or integers. See points for all alternatives.
layout
layout parameter passed to mfrow. Only used when study
is not "global"
size.title
size of the title
size.subtitle
size of the subtitle
size.xlabel
size of xlabel
size.ylabel
size of ylabel
size.axis
size of the axis
size.legend
size of the legend
size.legend.title
size of the legend title
legend.title
title of the legend
legend.position
position of the legend, one of "bottom", "left",
"top" and "right".
point.lwd
lwd of the points, used when ind.names =
FALSE
background
color the background by the predicted class, see
background.predict
ind.names
either a character vector of names for the individuals to
be plotted, or FALSE for no names. If TRUE, the row names of
the first (or second) data matrix is used as names (see Details).
Z.label
z axis titles (when style = '3d').
pch.levels
Only used when pch is different from col or
col.per.group, ie when pch creates a second factor. Only used
for the legend.
alpha
Semi-transparent colors (0 < 'alpha' < 1)
axes.box
for style '3d', argument to be set to either 'axes',
'box', 'bbox' or 'all', defining the shape of the box.
legend.title.pch
title of the second legend created by pch, if
any.
blocks
integer value or name(s) of block(s) to be plotted using the
GCCA module. "average" and "weighted.average" will create average and
weighted average plots, respectively. See details and examples.
Details
plotIndiv method makes scatter plot for individuals representation
depending on the subspace of projection. Each point corresponds to an
individual.
If ind.names=TRUE and row names is NULL, then
ind.names=1:n, where n is the number of individuals. Also, if
pch is an input, then ind.names is set to FALSE as we do not
show both names and shapes.
plotIndiv can have a two layers legend. This is especially convenient
when you have two grouping factors, such as a gender effect and a study
effect, and you want to highlight both simulatenously on the graphical
output. A first layer is coded by the group factor, the second by the
pch argument. When pch is missing, a single layer legend is
shown. If the group factor is missing, the col argument is
used to create the grouping factor group. When a second grouping
factor is needed and added via pch, pch needs to be a vector
of length the number of samples. In the case where pch is a vector or
length the number of groups, then we consider that the user wants a
different pch for each level of group. This leads to a single
layer legend and we merge col and pch. In the similar case
where pch is a single value, then this value is used to represent all
samples. See examples below for object of class plsda and splsda.
In the specific case of a single 'omics supervised model
(plsda, splsda), users can overlay prediction
results to sample plots in order to visualise the prediction areas of each
class, via the background input parameter. Note that this
functionality is only available for models with less than 2 components as
the surfaces obtained for higher order components cannot be projected onto a
2D representation in a meaningful way. For more details, see
background.predict
The argument block = 'average' averages the components from all blocks
to produce a consensus plot. The argument block='weighted.average' is
a weighted average of the components according to their correlation with the
outcome Y.
For customized plots (i.e. adding points, text), use the style = 'graphics'
(default is ggplot2).
Note: the ellipse options were borrowed from the ellipse.
Value
none
Author(s)
Ignacio González, Benoit Gautier, Francois Bartolo, Florian Rohart,
Kim-Anh Lê Cao, Al J Abadi
See Also
text, background.predict,
points and http://mixOmics.org/graphics for more details.
Examples
## plot of individuals for objects of class 'rcc'
# ----------------------------------------------------
data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene
nutri.res <- rcc(X, Y, ncomp = 3, lambda1 = 0.064, lambda2 = 0.008)
# default, panel plot for X and Y subspaces
plotIndiv(nutri.res)
## Not run:
# ellipse with respect to genotype in the XY space,
# names also indicate genotype
plotIndiv(nutri.res, rep.space= 'XY-variate',
ellipse = TRUE, ellipse.level = 0.9,
group = nutrimouse$genotype, ind.names = nutrimouse$genotype)
# ellipse with respect to genotype in the XY space, with legend
plotIndiv(nutri.res, rep.space= 'XY-variate', group = nutrimouse$genotype,
legend = TRUE)
# lattice style
plotIndiv(nutri.res, rep.space= 'XY-variate', group = nutrimouse$genotype,
legend = TRUE, style = 'lattice')
# classic style, in the Y space
plotIndiv(nutri.res, rep.space= 'Y-variate', group = nutrimouse$genotype,
legend = TRUE, style = 'graphics')
## plot of individuals for objects of class 'pls' or 'spls'
# ----------------------------------------------------
data(liver.toxicity)
X <- liver.toxicity$gene
Y <- liver.toxicity$clinic
toxicity.spls <- spls(X, Y, ncomp = 3, keepX = c(50, 50, 50),
keepY = c(10, 10, 10))
#default
plotIndiv(toxicity.spls)
# two layers legend: a first grouping with Time.Group and 'group'
# and a second with Dose.Group and 'pch'
plotIndiv(toxicity.spls, rep.space="X-variate", ind.name = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], # first factor
pch = as.numeric(factor(liver.toxicity$treatment$Dose.Group)), #second factor
pch.levels =liver.toxicity$treatment$Dose.Group,
legend = TRUE)
# indicating the centroid
plotIndiv(toxicity.spls, rep.space= 'X-variate', ind.names = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], centroid = TRUE)
# indicating the star and centroid
plotIndiv(toxicity.spls, rep.space= 'X-variate', ind.names = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], centroid = TRUE, star = TRUE)
# indicating the star and ellipse
plotIndiv(toxicity.spls, rep.space= 'X-variate', ind.names = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], centroid = TRUE,
star = TRUE, ellipse = TRUE)
# in the Y space, colors indicate time of necropsy, text is the dose
plotIndiv(toxicity.spls, rep.space= 'Y-variate',
group = liver.toxicity$treatment[, 'Time.Group'],
ind.names = liver.toxicity$treatment[, 'Dose.Group'],
legend = TRUE)
## plot of individuals for objects of class 'plsda' or 'splsda'
# ----------------------------------------------------
data(breast.tumors)
X <- breast.tumors$gene.exp
Y <- breast.tumors$sample$treatment
splsda.breast <- splsda(X, Y,keepX=c(10,10),ncomp=2)
# default option: note the outcome color is included by default!
plotIndiv(splsda.breast)
# also check ?background.predict for to visualise the prediction
# area with a plsda or splsda object!
# default option with no ind name: pch and color are set automatically
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2))
# default option with no ind name: pch and color are set automatically,
# with legend
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2), legend = TRUE)
# trying the different styles
plotIndiv(splsda.breast, ind.names = TRUE, comp = c(1, 2),
ellipse = TRUE, style = "ggplot2", cex = c(1, 1))
plotIndiv(splsda.breast, ind.names = TRUE, comp = c(1, 2),
ellipse = TRUE, style = "lattice", cex = c(1, 1))
# changing pch of the two groups
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = c(15,16), legend = TRUE)
# creating a second grouping factor with a pch of length 3,
# which is recycled to obtain a vector of length n
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = c(15,16,17), legend = TRUE)
#same thing as
pch.indiv = c(rep(15:17,15), 15, 16) # length n
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = pch.indiv, legend = TRUE)
# change the names of the second legend with pch.levels
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = 15:17, pch.levels = c("a","b","c"),legend = TRUE)
## plot of individuals for objects of class 'mint.plsda' or 'mint.splsda'
# ----------------------------------------------------
data(stemcells)
res = mint.splsda(X = stemcells$gene, Y = stemcells$celltype, ncomp = 2,
keepX = c(10, 5), study = stemcells$study)
plotIndiv(res)
#plot study-specific outputs for all studies
plotIndiv(res, study = "all.partial")
#plot study-specific outputs for study "2"
plotIndiv(res, study = "2")
## variable representation for objects of class 'sgcca' (or 'rgcca')
# ----------------------------------------------------
data(nutrimouse)
Y = unmap(nutrimouse$diet)
data = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid, Y = Y)
design1 = matrix(c(0,1,1,1,0,1,1,1,0), ncol = 3, nrow = 3, byrow = TRUE)
nutrimouse.sgcca <- wrapper.sgcca(X = data,
design = design1,
penalty = c(0.3, 0.5, 1),
ncomp = 3)
# default style: one panel for each block
plotIndiv(nutrimouse.sgcca)
# for the block 'lipid' with ellipse plots and legend, different styles
plotIndiv(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
ellipse = TRUE, ellipse.level = 0.5, blocks = "lipid", title = 'my plot')
plotIndiv(nutrimouse.sgcca, style = "lattice", group = nutrimouse$diet,
legend = TRUE, ellipse = TRUE, ellipse.level = 0.5, blocks = "lipid",
title = 'my plot')
plotIndiv(nutrimouse.sgcca, style = "graphics", group = nutrimouse$diet,
legend = TRUE, ellipse = TRUE, ellipse.level = 0.5, blocks = "lipid",
title = 'my plot')
## variable representation for objects of class 'sgccda'
# ----------------------------------------------------
# Note: the code differs from above as we use a 'supervised' GCCA analysis
data(nutrimouse)
Y = nutrimouse$diet
data = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid)
design1 = matrix(c(0,1,0,1), ncol = 2, nrow = 2, byrow = TRUE)
nutrimouse.sgccda1 <- wrapper.sgccda(X = data,
Y = Y,
design = design1,
ncomp = 2,
keepX = list(gene = c(10,10), lipid = c(15,15)))
# plotIndiv
# ----------
# displaying all blocks. bu default colors correspond to outcome Y
plotIndiv(nutrimouse.sgccda1)
# displaying only 2 blocks
plotIndiv(nutrimouse.sgccda1, blocks = c(1,2), group = nutrimouse$diet)
# include the average plot (average the components across datasets)
plotIndiv(nutrimouse.sgccda1, blocks = "average", group = nutrimouse$diet)
# include the weighted average plot (average of components weighted by
# correlation of each dataset with Y)
plotIndiv(
nutrimouse.sgccda1,
blocks = c("average", "weighted.average"),
group = nutrimouse$diet
)
# with some ellipse, legend and title
plotIndiv(nutrimouse.sgccda1, blocks = c(1,2), group = nutrimouse$diet,
ellipse = TRUE, legend = TRUE, title = 'my sample plot')
## End(Not run)
mixOmicsTeam/mixOmics documentation built on Nov. 19, 2024, 11:53 a.m.
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| plotIndiv | R Documentation |
Plot of Individuals (Experimental Units)
Description
This function provides scatter plots for individuals (experimental units) representation in (sparse)(I)PCA, (regularized)CCA, (sparse)PLS(DA) and (sparse)(R)GCCA(DA).
Usage
plotIndiv(object, ...)
## S3 method for class 'mint.pls'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'mint.spls'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'mint.plsda'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'mint.splsda'
plotIndiv(
object,
comp = NULL,
study = "global",
rep.space = c("X-variate", "XY-variate", "Y-variate", "multi"),
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'pca'
plotIndiv(
object,
comp = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
...
)
## S3 method for class 'mixo_pls'
plotIndiv(
object,
comp = NULL,
rep.space = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
background = NULL,
...
)
## S3 method for class 'sgcca'
plotIndiv(
object,
comp = NULL,
blocks = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
...
)
## S3 method for class 'rgcca'
plotIndiv(
object,
comp = NULL,
blocks = NULL,
ind.names = TRUE,
group,
col.per.group,
style = "ggplot2",
ellipse = FALSE,
ellipse.level = 0.95,
centroid = FALSE,
star = FALSE,
title = NULL,
subtitle,
legend = FALSE,
X.label = NULL,
Y.label = NULL,
Z.label = NULL,
abline = FALSE,
xlim = NULL,
ylim = NULL,
col,
cex,
pch,
pch.levels,
alpha = 0.2,
axes.box = "box",
layout = NULL,
size.title = rel(2),
size.subtitle = rel(1.5),
size.xlabel = rel(1),
size.ylabel = rel(1),
size.axis = rel(0.8),
size.legend = rel(1),
size.legend.title = rel(1.1),
legend.title = "Legend",
legend.title.pch = "Legend",
legend.position = "right",
point.lwd = 1,
...
)
Arguments
object |
object of class inherited from any mixOmics: |
... |
Optional arguments or type par can be added with |
comp |
integer vector of length two (or three to 3d). The components that will be used on the horizontal and the vertical axis respectively to project the individuals. |
study |
Indicates which study-specific outputs to plot. A character
vector containing some levels of |
rep.space |
For objects of class |
group |
factor indicating the group membership for each sample, useful
for ellipse plots. Coded as default for the supervised methods |
col.per.group |
character (or symbol) color to be used when 'group' is defined. Vector of the same length as the number of groups. |
style |
argument to be set to either |
ellipse |
Logical indicating if ellipse plots should be plotted. In the
non supervised objects |
ellipse.level |
Numerical value indicating the confidence level of
ellipse being plotted when |
centroid |
Logical indicating whether centroid points should be
plotted. In the non supervised objects |
star |
Logical indicating whether a star plot should be plotted, with
arrows starting from the centroid (see argument |
title |
set of characters indicating the title plot. |
subtitle |
subtitle for each plot, only used when several |
legend |
Logical. Whether the legend should be added. Default is FALSE. |
X.label |
x axis titles. |
Y.label |
y axis titles. |
abline |
should the vertical and horizontal line through the center be
plotted? Default set to |
xlim, ylim |
numeric list of vectors of length 2 and length =length(blocks), giving the x and y coordinates ranges. |
col |
character (or symbol) color to be used, possibly vector. |
cex |
numeric character (or symbol) expansion, possibly vector. |
pch |
plot character. A character string or a vector of single
characters or integers. See |
layout |
layout parameter passed to mfrow. Only used when |
size.title |
size of the title |
size.subtitle |
size of the subtitle |
size.xlabel |
size of xlabel |
size.ylabel |
size of ylabel |
size.axis |
size of the axis |
size.legend |
size of the legend |
size.legend.title |
size of the legend title |
legend.title |
title of the legend |
legend.position |
position of the legend, one of "bottom", "left", "top" and "right". |
point.lwd |
|
background |
color the background by the predicted class, see
|
ind.names |
either a character vector of names for the individuals to
be plotted, or |
Z.label |
z axis titles (when style = '3d'). |
pch.levels |
Only used when |
alpha |
Semi-transparent colors (0 < |
axes.box |
for style '3d', argument to be set to either |
legend.title.pch |
title of the second legend created by |
blocks |
integer value or name(s) of block(s) to be plotted using the GCCA module. "average" and "weighted.average" will create average and weighted average plots, respectively. See details and examples. |
Details
plotIndiv method makes scatter plot for individuals representation
depending on the subspace of projection. Each point corresponds to an
individual.
If ind.names=TRUE and row names is NULL, then
ind.names=1:n, where n is the number of individuals. Also, if
pch is an input, then ind.names is set to FALSE as we do not
show both names and shapes.
plotIndiv can have a two layers legend. This is especially convenient
when you have two grouping factors, such as a gender effect and a study
effect, and you want to highlight both simulatenously on the graphical
output. A first layer is coded by the group factor, the second by the
pch argument. When pch is missing, a single layer legend is
shown. If the group factor is missing, the col argument is
used to create the grouping factor group. When a second grouping
factor is needed and added via pch, pch needs to be a vector
of length the number of samples. In the case where pch is a vector or
length the number of groups, then we consider that the user wants a
different pch for each level of group. This leads to a single
layer legend and we merge col and pch. In the similar case
where pch is a single value, then this value is used to represent all
samples. See examples below for object of class plsda and splsda.
In the specific case of a single 'omics supervised model
(plsda, splsda), users can overlay prediction
results to sample plots in order to visualise the prediction areas of each
class, via the background input parameter. Note that this
functionality is only available for models with less than 2 components as
the surfaces obtained for higher order components cannot be projected onto a
2D representation in a meaningful way. For more details, see
background.predict
The argument block = 'average' averages the components from all blocks
to produce a consensus plot. The argument block='weighted.average' is
a weighted average of the components according to their correlation with the
outcome Y.
For customized plots (i.e. adding points, text), use the style = 'graphics' (default is ggplot2).
Note: the ellipse options were borrowed from the ellipse.
Value
none
Author(s)
Ignacio González, Benoit Gautier, Francois Bartolo, Florian Rohart, Kim-Anh Lê Cao, Al J Abadi
See Also
text, background.predict,
points and http://mixOmics.org/graphics for more details.
Examples
## plot of individuals for objects of class 'rcc'
# ----------------------------------------------------
data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene
nutri.res <- rcc(X, Y, ncomp = 3, lambda1 = 0.064, lambda2 = 0.008)
# default, panel plot for X and Y subspaces
plotIndiv(nutri.res)
## Not run:
# ellipse with respect to genotype in the XY space,
# names also indicate genotype
plotIndiv(nutri.res, rep.space= 'XY-variate',
ellipse = TRUE, ellipse.level = 0.9,
group = nutrimouse$genotype, ind.names = nutrimouse$genotype)
# ellipse with respect to genotype in the XY space, with legend
plotIndiv(nutri.res, rep.space= 'XY-variate', group = nutrimouse$genotype,
legend = TRUE)
# lattice style
plotIndiv(nutri.res, rep.space= 'XY-variate', group = nutrimouse$genotype,
legend = TRUE, style = 'lattice')
# classic style, in the Y space
plotIndiv(nutri.res, rep.space= 'Y-variate', group = nutrimouse$genotype,
legend = TRUE, style = 'graphics')
## plot of individuals for objects of class 'pls' or 'spls'
# ----------------------------------------------------
data(liver.toxicity)
X <- liver.toxicity$gene
Y <- liver.toxicity$clinic
toxicity.spls <- spls(X, Y, ncomp = 3, keepX = c(50, 50, 50),
keepY = c(10, 10, 10))
#default
plotIndiv(toxicity.spls)
# two layers legend: a first grouping with Time.Group and 'group'
# and a second with Dose.Group and 'pch'
plotIndiv(toxicity.spls, rep.space="X-variate", ind.name = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], # first factor
pch = as.numeric(factor(liver.toxicity$treatment$Dose.Group)), #second factor
pch.levels =liver.toxicity$treatment$Dose.Group,
legend = TRUE)
# indicating the centroid
plotIndiv(toxicity.spls, rep.space= 'X-variate', ind.names = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], centroid = TRUE)
# indicating the star and centroid
plotIndiv(toxicity.spls, rep.space= 'X-variate', ind.names = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], centroid = TRUE, star = TRUE)
# indicating the star and ellipse
plotIndiv(toxicity.spls, rep.space= 'X-variate', ind.names = FALSE,
group = liver.toxicity$treatment[, 'Time.Group'], centroid = TRUE,
star = TRUE, ellipse = TRUE)
# in the Y space, colors indicate time of necropsy, text is the dose
plotIndiv(toxicity.spls, rep.space= 'Y-variate',
group = liver.toxicity$treatment[, 'Time.Group'],
ind.names = liver.toxicity$treatment[, 'Dose.Group'],
legend = TRUE)
## plot of individuals for objects of class 'plsda' or 'splsda'
# ----------------------------------------------------
data(breast.tumors)
X <- breast.tumors$gene.exp
Y <- breast.tumors$sample$treatment
splsda.breast <- splsda(X, Y,keepX=c(10,10),ncomp=2)
# default option: note the outcome color is included by default!
plotIndiv(splsda.breast)
# also check ?background.predict for to visualise the prediction
# area with a plsda or splsda object!
# default option with no ind name: pch and color are set automatically
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2))
# default option with no ind name: pch and color are set automatically,
# with legend
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2), legend = TRUE)
# trying the different styles
plotIndiv(splsda.breast, ind.names = TRUE, comp = c(1, 2),
ellipse = TRUE, style = "ggplot2", cex = c(1, 1))
plotIndiv(splsda.breast, ind.names = TRUE, comp = c(1, 2),
ellipse = TRUE, style = "lattice", cex = c(1, 1))
# changing pch of the two groups
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = c(15,16), legend = TRUE)
# creating a second grouping factor with a pch of length 3,
# which is recycled to obtain a vector of length n
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = c(15,16,17), legend = TRUE)
#same thing as
pch.indiv = c(rep(15:17,15), 15, 16) # length n
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = pch.indiv, legend = TRUE)
# change the names of the second legend with pch.levels
plotIndiv(splsda.breast, ind.names = FALSE, comp = c(1, 2),
pch = 15:17, pch.levels = c("a","b","c"),legend = TRUE)
## plot of individuals for objects of class 'mint.plsda' or 'mint.splsda'
# ----------------------------------------------------
data(stemcells)
res = mint.splsda(X = stemcells$gene, Y = stemcells$celltype, ncomp = 2,
keepX = c(10, 5), study = stemcells$study)
plotIndiv(res)
#plot study-specific outputs for all studies
plotIndiv(res, study = "all.partial")
#plot study-specific outputs for study "2"
plotIndiv(res, study = "2")
## variable representation for objects of class 'sgcca' (or 'rgcca')
# ----------------------------------------------------
data(nutrimouse)
Y = unmap(nutrimouse$diet)
data = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid, Y = Y)
design1 = matrix(c(0,1,1,1,0,1,1,1,0), ncol = 3, nrow = 3, byrow = TRUE)
nutrimouse.sgcca <- wrapper.sgcca(X = data,
design = design1,
penalty = c(0.3, 0.5, 1),
ncomp = 3)
# default style: one panel for each block
plotIndiv(nutrimouse.sgcca)
# for the block 'lipid' with ellipse plots and legend, different styles
plotIndiv(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
ellipse = TRUE, ellipse.level = 0.5, blocks = "lipid", title = 'my plot')
plotIndiv(nutrimouse.sgcca, style = "lattice", group = nutrimouse$diet,
legend = TRUE, ellipse = TRUE, ellipse.level = 0.5, blocks = "lipid",
title = 'my plot')
plotIndiv(nutrimouse.sgcca, style = "graphics", group = nutrimouse$diet,
legend = TRUE, ellipse = TRUE, ellipse.level = 0.5, blocks = "lipid",
title = 'my plot')
## variable representation for objects of class 'sgccda'
# ----------------------------------------------------
# Note: the code differs from above as we use a 'supervised' GCCA analysis
data(nutrimouse)
Y = nutrimouse$diet
data = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid)
design1 = matrix(c(0,1,0,1), ncol = 2, nrow = 2, byrow = TRUE)
nutrimouse.sgccda1 <- wrapper.sgccda(X = data,
Y = Y,
design = design1,
ncomp = 2,
keepX = list(gene = c(10,10), lipid = c(15,15)))
# plotIndiv
# ----------
# displaying all blocks. bu default colors correspond to outcome Y
plotIndiv(nutrimouse.sgccda1)
# displaying only 2 blocks
plotIndiv(nutrimouse.sgccda1, blocks = c(1,2), group = nutrimouse$diet)
# include the average plot (average the components across datasets)
plotIndiv(nutrimouse.sgccda1, blocks = "average", group = nutrimouse$diet)
# include the weighted average plot (average of components weighted by
# correlation of each dataset with Y)
plotIndiv(
nutrimouse.sgccda1,
blocks = c("average", "weighted.average"),
group = nutrimouse$diet
)
# with some ellipse, legend and title
plotIndiv(nutrimouse.sgccda1, blocks = c(1,2), group = nutrimouse$diet,
ellipse = TRUE, legend = TRUE, title = 'my sample plot')
## End(Not run)
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