plotFeatureScatter {clusterExperiment} | R Documentation

## Plot scatter plot of feature values colored by cluster

### Description

Plot a scatter plot of the (transformed) values for a set of gene expression values, colored by cluster

### Usage

    ## S4 method for signature 'ClusterExperiment,character'
    plotFeatureScatter(object, features, ...)

    ## S4 method for signature 'ClusterExperiment,numeric'
    plotFeatureScatter(
      object,
      features,
      whichCluster = "primary",
      plotUnassigned = TRUE,
      unassignedColor = "grey",
      missingColor = "white",
      whichAssay = 1,
      legendLocation = NA,
      jitterFactor = NA,
      ...
    )

### Arguments

`object` | a ClusterExperiment object
`features` | the indices of the features (either numeric or character matching rownames of object) to be plotted.
`...` | arguments passed to `boxplot`
`whichCluster` | argument that can be a single numeric or character value indicating the single clustering to be used. Giving values that result in more than one clustering will result in an error. See details of `getClusterIndex`.
`plotUnassigned` | whether to plot the unassigned samples as a cluster (either -1 or -2)
`unassignedColor` | If not NULL, should be character value giving the color for unassigned (-2) samples (overrides `clusterLegend`) default.
`missingColor` | If not NULL, should be character value giving the color for missing (-2) samples (overrides `clusterLegend`) default.
`whichAssay` | numeric or character specifying which assay to use. See `assay` for details.
`legendLocation` | character value passed to `location` argument of `plotClusterLegend` indicating where to put the legend. If NA, legend will not be plotted.
`jitterFactor` | numeric. If NA, no jittering is done. Otherwise, passed to `factor` of function `jitter` (useful for low counts)

### Value

returns invisibly the results of `pairs` or `plot` command.

### Examples

    data(simData)
    #Create a ClusterExperiment object
    cl <- clusterMany(simData, nReducedDims=c(5, 10, 50), reducedDim="PCA",
       clusterFunction="pam", ks=2:4, findBestK=c(TRUE,FALSE),
       removeSil=c(TRUE,FALSE), makeMissingDiss=TRUE)
    #give names to the clusters
    cl<-renameClusters(cl, whichCluster=1,
       value=letters[1:nClusters(cl)[1]])
    plotFeatureScatter(cl,feature=1:2,pch=19,legendLocation="topright")

[Package clusterExperiment version 2.12.0 Index]