plotDiablo {mixOmics} | R Documentation

## Graphical output for the DIABLO framework

### 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)

[Package mixOmics version 6.16.3 Index]