# NOT RUN {
## object of class 'spls'
# --------------------------
data(liver.toxicity)
X = liver.toxicity$gene
Y = liver.toxicity$clinic
toxicity.spls = spls(X, Y, ncomp = 2, keepX = c(50, 50),
keepY = c(10, 10))
plotLoadings(toxicity.spls)
# with xlim
xlim = matrix(c(-0.1,0.3, -0.4,0.6), nrow = 2, byrow = TRUE)
plotLoadings(toxicity.spls, xlim = xlim)
## object of class 'splsda'
# --------------------------
data(liver.toxicity)
X = as.matrix(liver.toxicity$gene)
Y = as.factor(liver.toxicity$treatment[, 4])
splsda.liver = splsda(X, Y, ncomp = 2, keepX = c(20, 20))
# contribution on comp 1, based on the median.
# Colors indicate the group in which the median expression is maximal
plotLoadings(splsda.liver, comp = 1, method = 'median')
plotLoadings(splsda.liver, comp = 1, method = 'median', contrib = "max")
# contribution on comp 2, based on median.
#Colors indicate the group in which the median expression is maximal
plotLoadings(splsda.liver, comp = 2, method = 'median', contrib = "max")
# contribution on comp 2, based on median.
# Colors indicate the group in which the median expression is minimal
plotLoadings(splsda.liver, comp = 2, method = 'median', contrib = 'min')
# changing the name to gene names
# if the user input a name.var but names(name.var) is NULL,
# then a warning will be output and assign names of name.var to colnames(X)
# this is to make sure we can match the name of the selected variables to the contribution plot.
name.var = liver.toxicity$gene.ID[, 'geneBank']
length(name.var)
plotLoadings(splsda.liver, comp = 2, method = 'median', name.var = name.var,
title = "Liver data", contrib = "max")
# if names are provided: ok, even when NAs
name.var = liver.toxicity$gene.ID[, 'geneBank']
names(name.var) = rownames(liver.toxicity$gene.ID)
plotLoadings(splsda.liver, comp = 2, method = 'median',
name.var = name.var, size.name = 0.5, contrib = "max")
#missing names of some genes? complete with the original names
plotLoadings(splsda.liver, comp = 2, method = 'median',
name.var = name.var, size.name = 0.5,complete.name.var=TRUE, contrib = "max")
# look at the contribution (median) for each variable
plot.contrib = plotLoadings(splsda.liver, comp = 2, method = 'median', plot = FALSE,
contrib = "max")
head(plot.contrib$contrib)
# change the title of the legend and title name
plotLoadings(splsda.liver, comp = 2, method = 'median', legend.title = 'Time',
title = 'Contribution plot', contrib = "max")
# no legend
plotLoadings(splsda.liver, comp = 2, method = 'median', legend = FALSE, contrib = "max")
# change the color of the legend
plotLoadings(splsda.liver, comp = 2, method = 'median', legend.color = c(1:4), contrib = "max")
# object 'splsda multilevel'
# -----------------
# }
# NOT RUN {
data(vac18)
X = vac18$genes
Y = vac18$stimulation
# sample indicates the repeated measurements
sample = vac18$sample
stimul = vac18$stimulation
# multilevel sPLS-DA model
res.1level = splsda(X, Y = stimul, ncomp = 3, multilevel = sample,
keepX = c(30, 137, 123))
name.var = vac18$tab.prob.gene[, 'Gene']
names(name.var) = colnames(X)
plotLoadings(res.1level, comp = 2, method = 'median', legend.title = 'Stimu',
name.var = name.var, size.name = 0.2, contrib = "max")
# too many transcripts? only output the top ones
plotLoadings(res.1level, comp = 2, method = 'median', legend.title = 'Stimu',
name.var = name.var, size.name = 0.5, ndisplay = 60, contrib = "max")
# }
# NOT RUN {
# object 'plsda'
# ----------------
# }
# NOT RUN {
# breast tumors
# ---
data(breast.tumors)
X = breast.tumors$gene.exp
Y = breast.tumors$sample$treatment
plsda.breast = plsda(X, Y, ncomp = 2)
name.var = as.character(breast.tumors$genes$name)
names(name.var) = colnames(X)
# with gene IDs, showing the top 60
plotLoadings(plsda.breast, contrib = 'max', comp = 1, method = 'median',
ndisplay = 60,
name.var = name.var,
size.name = 0.6,
legend.color = color.mixo(1:2))
# }
# NOT RUN {
# liver toxicity
# ---
# }
# NOT RUN {
data(liver.toxicity)
X = liver.toxicity$gene
Y = liver.toxicity$treatment[, 4]
plsda.liver = plsda(X, Y, ncomp = 2)
plotIndiv(plsda.liver, ind.names = Y, ellipse = TRUE)
name.var = liver.toxicity$gene.ID[, 'geneBank']
names(name.var) = rownames(liver.toxicity$gene.ID)
plotLoadings(plsda.liver, contrib = 'max', comp = 1, method = 'median', ndisplay = 100,
name.var = name.var, size.name = 0.4,
legend.color = color.mixo(1:4))
# }
# NOT RUN {
# object 'sgccda'
# ----------------
# }
# NOT RUN {
data(nutrimouse)
Y = nutrimouse$diet
data = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid)
design = matrix(c(0,1,1,1,0,1,1,1,0), ncol = 3, nrow = 3, byrow = TRUE)
nutrimouse.sgccda = wrapper.sgccda(X = data,
Y = Y,
design = design,
keepX = list(gene = c(10,10), lipid = c(15,15)),
ncomp = 2,
scheme = "centroid")
plotLoadings(nutrimouse.sgccda,block=2)
plotLoadings(nutrimouse.sgccda,block="gene")
# }
# NOT RUN {
# object 'mint.splsda'
# ----------------
data(stemcells)
data = stemcells$gene
type.id = stemcells$celltype
exp = stemcells$study
res = mint.splsda(X = data, Y = type.id, ncomp = 3, keepX = c(10,5,15), study = exp)
plotLoadings(res)
plotLoadings(res, contrib = "max")
plotLoadings(res, contrib = "min", study = 1:4,comp=2)
# combining different plots by setting a layout of 2 rows and 4columns.
# Note that the legend accounts for a subplot so 4columns instead of 2.
plotLoadings(res,contrib="min",study=c(1,2,3),comp=2, layout = c(2,4))
plotLoadings(res,contrib="min",study="global",comp=2)
# }
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