plotDiablo: Graphical output for the DIABLO framework

In mixOmics: Omics Data Integration Project

Description

Function to visualise correlation between components from different data sets

Usage

plotDiablo(
  object,
  ncomp = 1,
  legend = TRUE,
  legend.ncol,
  col.per.group = NULL,
  ...
)

## S3 method for class 'sgccda'
plot(x, ...)

Arguments

object, 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$ncomp.
legend	Logical. Whether the legend should be added. Default is TRUE.
legend.ncol	Number of columns for the legend. Default to min(5,nlevels(x$Y)).
col.per.group	A named character of colours for each group class representation. Its names must match the levels of object$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

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)

mixOmics documentation built on April 15, 2021, 6:01 p.m.