plotIndiv {mixOmics} | R Documentation |
This function provides scatter plots for individuals (experimental units) representation in (sparse)(I)PCA, (regularized)CCA, (sparse)PLS(DA) and (sparse)(R)GCCA(DA).
## 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 'mint.spls' plotIndiv(object, comp = NULL, study = "global", rep.space = NULL, 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, ... ) ## 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, ... )
object |
object of class inherited from any mixOmics: |
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. |
rep.space |
For objects inherited from |
blocks |
integer value of name of a block to be plotted using the GCCA module. See examples. |
study |
Indicates which study-specific outputs to plot. A character vector containing some levels of |
ind.names |
either a character vector of names for the individuals to be plotted,
or |
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 than the number of groups. |
style |
argument to be set to either |
ellipse |
boolean 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 |
boolean indicating whether centroid points should be plotted. In the non supervised objects |
star |
boolean 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 |
boolean. Whether the legend should be added. Default is FALSE. |
X.label |
x axis titles. |
Y.label |
y axis titles. |
Z.label |
z axis titles (when style = '3d'). |
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 |
pch.levels |
Only used when |
alpha |
Semi-transparent colors (0 < |
axes.box |
for style '3d', argument to be set to either |
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.title.pch |
title of the second legend created by |
legend.position |
position of the legend, one of "bottom", "left", "top" and "right". |
point.lwd |
|
background |
color the background by the predicted class, see |
... |
external arguments or type par can be added with |
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
For customized plots (i.e. adding points, text), use the style = 'graphics' (default is ggplot2).
Note: the ellipse options were borrowed from the ellipse.
none
Ignacio González, Benoit Gautier, Francois Bartolo, Florian Rohart
text
, background.predict
, points
and http://mixOmics.org/graphics for more details.
## 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, only in the X space 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, #levels of the second factor, for the legend 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, scheme = "horst") # 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)), scheme = "centroid") # 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$diet) # with some ellipse, legend and title plotIndiv(nutrimouse.sgccda1, blocks = c(1,2), group = nutrimouse$diet, ellipse = TRUE, legend = TRUE, title = 'my sample plot') ## End(Not run)