plotArrow: Arrow sample plot
In ajabadi/mixOmics2: Omics Data Integration Project

Description Usage Arguments Details Value Author(s) References See Also Examples

Represents samples from multiple coordinates.

plotArrow(object, comp = NULL, abline = FALSE, xlim = NULL,
  ylim = NULL, group = NULL, col, cex, pch, title = NULL,
  plot.arrows = TRUE, legend = FALSE, X.label = NULL,
  Y.label = NULL, ind.names = FALSE, position.names = "centroid")

`object`	object of class inheriting from mixOmics: `PLS, sPLS, rCC, rGCCA, sGCCA, sGCCDA`
`comp`	integer vector of length two indicating the components represented on the horizontal and the vertical axis to project the individuals.
`abline`	should the vertical and horizontal line through the center be plotted? Default set to `FALSE`
`xlim`	the ranges to be encompassed by the x axis, if `NULL` they are computed.
`ylim`	the ranges to be encompassed by the y axis, if `NULL` they are computed.
`group`	factor indicating the group membership for each sample. Coded as default for the supervised method `sGCCDA, sPLSDA`, but needs to be input for the unsupervised methods `PLS, sPLS, rCC, rGCCA, sGCCA`
`col`	character (or symbol) color to be used, color vector also possible.
`cex`	numeric character (or symbol) expansion, , color vector also possible.
`pch`	plot character. A character string or a vector of single characters or integers. See `points` for all alternatives.
`title`	set of characters for the title plot.
`plot.arrows`	boolean. Whether arrows should be added or not. Default is `TRUE`.
`legend`	boolean. Whether the legend should be added. Only for the supervised methods and if group!=NULL. Default is `FALSE`.
`X.label`	x axis titles.
`Y.label`	y axis titles.
`ind.names`	If `TRUE`, the row names of the first (or second) data matrix are used as sample names (see Details). Can be a vector of length the sample size to display sample names.
`position.names`	One of `"centroid", "start", "end"`. Define where sample names are plotted when `ind.names=TRUE`. In a multiblock analysis, centroid and start will display similarly.

Graphical of the samples (individuals) is displayed in a superimposed manner where each sample will be indicated using an arrow. The start of the arrow indicates the location of the sample in X in one plot, and the tip the location of the sample in Y in the other plot.

For objects of class "GCCA" and if there are more than 3 blocks, the start of the arrow indicates the centroid between all data sets for a given individual and the tips of the arrows the location of that individual in each block.

Short arrows indicate a strong agreement between the matching data sets, long arrows a disagreement between the matching data sets.

none

Francois Bartolo, Kim-Anh Lê Cao.

Lê Cao, K.-A., Martin, P.G.P., Robert-Granie, C. and Besse, P. (2009). Sparse canonical methods for biological data integration: application to a cross-platform study. BMC Bioinformatics 10:34.

arrows, text, points and http://mixOmics.org/graphics for more details.

## plot of individuals for objects of class 'rcc'
# ----------------------------------------------------
dev.off()
X <- nutrimouse$lipid
Y <- nutrimouse$gene
nutri.res <- rcc(X, Y, ncomp = 3, lambda1 = 0.064, lambda2 = 0.008)

plotArrow(nutri.res)

# names indicate genotype
plotArrow(nutri.res,
group = nutrimouse$genotype, ind.names = nutrimouse$genotype)


plotArrow(nutri.res, group = nutrimouse$genotype,
legend = TRUE)


## Not run: 
## plot of individuals for objects of class 'pls' or 'spls'
# ----------------------------------------------------
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
plotArrow(toxicity.spls)


# colors indicate time of necropsy, text is the dose
plotArrow(toxicity.spls,  group = liver.toxicity$treatment[, 'Time.Group'],
ind.names  = liver.toxicity$treatment[, 'Dose.Group'],
legend = TRUE)

# colors indicate time of necropsy, text is the dose, label at start of arrow
plotArrow(toxicity.spls,  group = liver.toxicity$treatment[, 'Time.Group'],
ind.names  = liver.toxicity$treatment[, 'Dose.Group'],
legend = TRUE, position.names = 'start')

## variable representation for objects of class 'sgcca' (or 'rgcca')
# ----------------------------------------------------
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 = "centroid")

# default style: same color for all samples
plotArrow(nutrimouse.sgcca)


plotArrow(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
title = 'my plot')

# ind.names to visualise the unique individuals
plotArrow(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
title = 'my plot', ind.names = TRUE)

# ind.names to visualise the unique individuals
plotArrow(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
title = 'my plot', ind.names = TRUE,position.names   = 'start')

plotArrow(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
title = 'my plot', ind.names = TRUE,position.names   = 'end')

# ind.names indicates the diet
plotArrow(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
title = 'my plot', ind.names = nutrimouse$diet, position.names= 'start')

# ind.names to visualise the unique individuals, start position
plotArrow(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
title = 'my plot', ind.names = TRUE, position.names   = 'start')

# end position
plotArrow(nutrimouse.sgcca, group = nutrimouse$diet, legend =TRUE,
title = 'my plot', ind.names = TRUE, position.names   = 'end')


## variable representation for objects of class 'sgccda'
# ----------------------------------------------------
# Note: the code differs from above as we use a 'supervised' GCCA analysis
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")


#  default colors correspond to outcome Y
plotArrow(nutrimouse.sgccda1)


# with legend and title and indiv ID
plotArrow(nutrimouse.sgccda1,  legend = TRUE, title = 'my sample plot',
ind.names = TRUE, position.names = 'start')


## End(Not run)