compoundsCluster-class: Compounds cluster class
In rickhelmus/patRoon: Workflows for Mass-Spectrometry Based Non-Target Analysis

compoundsCluster-class

R Documentation

Compounds cluster class

Description

Objects from this class are used to store hierarchical clustering data of candidate structures within compounds objects.

Usage

## S4 method for signature 'compoundsCluster'
clusters(obj)

## S4 method for signature 'compoundsCluster'
cutClusters(obj)

## S4 method for signature 'compoundsCluster'
clusterProperties(obj)

## S4 method for signature 'compoundsCluster'
groupNames(obj)

## S4 method for signature 'compoundsCluster'
length(x)

## S4 method for signature 'compoundsCluster'
lengths(x, use.names = TRUE)

## S4 method for signature 'compoundsCluster'
show(object)

## S4 method for signature 'compoundsCluster,ANY,missing,missing'
x[i, j, ..., drop = TRUE]

## S4 method for signature 'compoundsCluster'
treeCut(obj, k = NULL, h = NULL, groupName)

## S4 method for signature 'compoundsCluster'
treeCutDynamic(obj, maxTreeHeight, deepSplit, minModuleSize, groupName)

## S4 method for signature 'compoundsCluster,missing'
plot(
  x,
  ...,
  groupName,
  pal = "Paired",
  colourBranches = lengths(x)[groupName] < 50,
  showLegend = lengths(x)[groupName] < 20
)

## S4 method for signature 'compoundsCluster'
getMCS(obj, groupName, cluster)

## S4 method for signature 'compoundsCluster'
plotStructure(
  obj,
  groupName,
  cluster,
  width = 500,
  height = 500,
  withTitle = TRUE
)

## S4 method for signature 'compoundsCluster'
plotSilhouettes(obj, kSeq, groupName, pch = 16, type = "b", ...)

Arguments

`obj`, `x`, `object`	A `compoundsCluster` object.
`use.names`	A logical value specifying whether the returned vector should be named with the feature group names.
`i`	For `[`: A numeric or character value which is used to select feature groups by their index or name, respectively (for the order/names see `groupNames()`). Can also be logical to perform logical selection (similar to regular vectors). If missing all feature groups are selected.
`...`	Further arguments passed directly to the plotting function (`plot` or `plot.dendrogram`).
`drop`, `j`	ignored.
`k`, `h`	Desired number of clusters or tree height to be used for cutting the dendrogram, respecitively. One or the other must be specified. Analogous to `cutree`.
`groupName`	A character specifying the feature group name.
`maxTreeHeight`, `deepSplit`, `minModuleSize`	Arguments used by `cutreeDynamicTree`.
`pal`	Colour palette to be used from RColorBrewer.
`colourBranches`	Whether branches from cut clusters (and their labels) should be coloured. Might be slow with large numbers of clusters, hence, the default is only `TRUE` when this is not the case.
`showLegend`	If `TRUE` and `colourBranches` is also `TRUE` then a legend will be shown which outlines cluster numbers and their colours. By default `TRUE` for small amount of clusters to avoid overflowing the plot.
`cluster`	A numeric value specifying the cluster.
`width`, `height`	The dimensions (in pixels) of the raster image that should be plotted.
`withTitle`	A logical value specifying whether a title should be added.
`kSeq`	An integer vector containing the sequence that should be used for average silhouette width calculation.
`pch`, `type`	Passed to `plot`.

Details

Objects from this type are returned by the compounds method for makeHCluster.

Value

cutTree and cutTreeDynamic return the modified compoundsCluster object.

getMCS returns an rcdk molecule object (IAtomContainer).

Methods (by generic)

clusters(compoundsCluster): Accessor method to the clusters slot. Returns a list that contains for each feature group an object as returned by hclust.
cutClusters(compoundsCluster): Accessor method to the cutClusters slot. Returns a list that contains for each feature group a vector with cluster membership for each candidate (format as cutree).
clusterProperties(compoundsCluster): Returns a list with properties on how the clustering was performed.
groupNames(compoundsCluster): returns a character vector with the names of the feature groups for which data is present in this object.
length(compoundsCluster): Returns the total number of clusters.
lengths(compoundsCluster): Returns a vector with the number of clusters per feature group.
show(compoundsCluster): Show summary information for this object.
x[i: Subset on feature groups.
treeCut(compoundsCluster): Manually (re-)cut a dendrogram that was generated for a feature group.
treeCutDynamic(compoundsCluster): Automatically (re-)cut a dendrogram that was generated for a feature group using the cutreeDynamicTree function from dynamicTreeCut.
plot(x = compoundsCluster, y = missing): Plot the dendrogram for clustered compounds of a feature group. Clusters are highlighted using dendextend.
getMCS(compoundsCluster): Calculates the maximum common substructure (MCS) for all candidate structures within a specified cluster. This method uses the get.mcs function from rcdk.
plotStructure(compoundsCluster): Plots the maximum common substructure (MCS) for all candidate structures within a specified cluster.
plotSilhouettes(compoundsCluster): Plots the average silhouette width when the clusters are cut by a sequence of k numbers. The k value with the highest value (marked in the plot) may be considered as the optimal number of clusters.

Slots

clusters: A list with hclust objects for each feature group.
dists: A list with distance matrices for each feature group.
SMILES: A list containing a vector with SMILES for all candidate structures per feature group.
cutClusters: A list with assigned clusters for all candidates per feature group (same format as what cutree returns).
properties: A list containing general properties and parameters used for clustering.