Graphical output for the DIABLO framework
Function to visualise correlation between components from different data sets
plotDiablo( object, ncomp = 1, legend = TRUE, legend.ncol, col.per.group = NULL, ... ) ## S3 method for class 'sgccda' plot(x, ...)
object, x |
object of class inheriting from |
ncomp |
Which component to plot calculated from each data set. Has to
be lower than the minimum of |
legend |
Logical. Whether the legend should be added. Default is TRUE. |
legend.ncol |
Number of columns for the legend. Default to
|
col.per.group |
A named character of colours for each group class representation. Its names must match the levels of object$Y. |
... |
not used |
The function uses a plot.data.frame to plot the component ncomp
calculated from each data set to visualise whether DIABLO (block.splsda) is
successful at maximising the correlation between each data sets' component.
The lower triangular panel indicated the Pearson's correlation coefficient,
the upper triangular panel the scatter plot.
none
Amrit Singh, Florian Rohart, Kim-Anh Lê Cao, Al J Abadi
Singh A., Shannon C., Gautier B., Rohart F., Vacher M., Tebbutt S. and Lê Cao K.A. (2019), DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays, Bioinformatics, Volume 35, Issue 17, 1 September 2019, Pages 3055–3062.
block.splsda and http://www.mixOmics.org/mixDIABLO
for more details.
data('breast.TCGA')
Y = breast.TCGA$data.train$subtype
data = list(mrna = breast.TCGA$data.train$mrna,
mirna = breast.TCGA$data.train$mirna, prot = breast.TCGA$data.train$protein)
# set number of component per data set
ncomp = 3
# set number of variables to select, per component and per data set (arbitrarily set)
list.keepX = list(mrna = rep(20, 3), mirna = rep(10,3), prot = rep(10,3))
# DIABLO using a full design where every block is connected
BC.diablo = block.splsda(X = data, Y = Y, ncomp = ncomp, keepX = list.keepX, design = 'full')
## default col.per.group
plotDiablo(BC.diablo, ncomp = 1, legend = TRUE, col.per.group = NULL)
## custom col.per.group
col.per.group <- color.mixo(1:3)
names(col.per.group) <- levels(Y)
plotDiablo(BC.diablo, ncomp = 1, legend = TRUE, col.per.group = col.per.group)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.