ClustDist-class {pRoloc} | R Documentation

## Class `"ClustDist"`

### Description

The `ClustDist` summaries algorithm information, from running the `clustDist` function, such as the number of k's tested for the kmeans, and mean and normalised pairwise (Euclidean) distances per numer of component clusters tested.

### Objects from the Class

Object of this class are created with the `clustDist` function.

### Slots

`k`:

  Object of class `"numeric"` storing the number of k clusters tested.

`dist`:

  Object of class `"list"` storing the list of distance matrices.

`term`:

  Object of class `"character"` describing GO term name.

`id`:

  Object of class `"character"` describing the GO term ID.

`nrow`:

  Object of class `"numeric"` showing the number of instances in the set

`clustsz`:

  Object of class `"list"` describing the number of instances for each cluster for each k tested

`components`:

  Object of class `"vector"` storing the class membership of each protein for each k tested.

`fcol`:

  Object of class `"character"` showing the feature column name in the corresponding `MSnSet` where the protein set information is stored.

### Methods

plot

  Plots the kmeans clustering results.

show

  Shows the object.

### Author(s)

Lisa M Breckels <lms79@cam.ac.uk>

### Examples

      showClass("ClustDist")

      library('pRolocdata')
      data(dunkley2006)
      par <- setAnnotationParams(inputs =
                        c("Arabidopsis thaliana genes",
                          "Gene stable ID"))

      ## add protein set/annotation information
      xx <- addGoAnnotations(dunkley2006, par)

      ## filter
      xx <- filterMinMarkers(xx, n = 50)
      xx <- filterMaxMarkers(xx, p = .25)

      ## get distances for protein sets
      dd <- clustDist(xx)

      ## plot clusters for first 'ClustDist' object
      ## in the 'ClustDistList'
      plot(dd[[1]], xx)

      ## plot distances for all protein sets
      plot(dd)

[Package pRoloc version 1.30.0 Index]