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Class "ClustDist"

ClustDist-class.Rd

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

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

Examples

  showClass("ClustDist")
#> Class "ClustDist" [package "pRoloc"]
#> 
#> Slots:
#>                                                                         
#> Name:           k       dist       term         id       nrow    clustsz
#> Class:    numeric       list  character  character    numeric       list
#>                             
#> Name:  components       fcol
#> Class:     vector  character
  
  library('pRolocdata')
#> 
#> This is pRolocdata version 1.45.1.
#> Use 'pRolocdata()' to list available data sets.
  data(dunkley2006)
  par <- setAnnotationParams(inputs =
                    c("Arabidopsis thaliana genes",
                      "Gene stable ID"))
#> Using species Arabidopsis thaliana genes (TAIR10)
#> Warning: Ensembl will soon enforce the use of https.
#> Ensure the 'host' argument includes "https://"
#> Using feature type Gene stable ID(s) [e.g. AT1G01010]
#> Connecting to Biomart...
#> Warning: Ensembl will soon enforce the use of https.
#> Ensure the 'host' argument includes "https://"
                    
  ## add protein set/annotation information                  
  xx <- addGoAnnotations(dunkley2006, par)
#> Loading required namespace: GO.db
#> 
  
  ## filter
  xx <- filterMinMarkers(xx, n = 50)
#> Retaining 3 out of 79 in GOAnnotations
  xx <- filterMaxMarkers(xx, p = .25)
#> Retaining 2 out of 3 in GOAnnotations
  
  ## get distances for protein sets
  dd <- clustDist(xx)
#> 
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  ## plot clusters for first 'ClustDist' object 
  ## in the 'ClustDistList'
  plot(dd[[1]], xx)

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