plotDiablo: Graphical output for the DIABLO framework

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

View source: R/plotDiablo.R

Description

Function to visualise correlation between components from different data sets

Usage

1
2
3
4
plotDiablo(x, ncomp = 1, legend = TRUE, legend.ncol, ...)

## S3 method for class 'sgccda'
plot(x, ncomp = 1, legend = TRUE, legend.ncol, ...)

Arguments

x

object of class inheriting from "block.splsda".

ncomp

Which component to plot calculated from each data set. Has to be lower than the minimum of object$ncomp

legend

boolean. Whether the legend should be added. Default is TRUE.

legend.ncol

Number of columns for the legend. Default to min(5,nlevels(x$Y))

...

not used

Details

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.

Value

none

Author(s)

Amrit Singh, Florian Rohart, Kim-Anh Lê Cao, Al J Abadi

References

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.

See Also

block.splsda and http://www.mixOmics.org/mixDIABLO for more details.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
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))

# set up a full design where every block is connected
design = matrix(1, ncol = length(data), nrow = length(data),
dimnames = list(names(data), names(data)))
diag(design) =  0
design

BC.diablo = block.splsda(X = data, Y = Y, ncomp = ncomp, keepX = list.keepX, design = design)
plotDiablo(BC.diablo, ncomp = 1)

Example output

Loading required package: MASS
Loading required package: lattice
Loading required package: ggplot2

Loaded mixOmics 6.3.2

Thank you for using mixOmics!

How to apply our methods: http://www.mixOmics.org for some examples.
Questions or comments: email us at mixomics[at]math.univ-toulouse.fr  
Any bugs? https://bitbucket.org/klecao/package-mixomics/issues
Cite us:  citation('mixOmics')
Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
      mrna mirna prot
mrna     0     1    1
mirna    1     0    1
prot     1     1    0
Design matrix has changed to include Y; each block will be linked to Y.

mixOmics documentation built on Nov. 8, 2020, 11:12 p.m.