R: Adaptive Branch Pruning of Hierarchical Clustering...

cutreeDynamic {dynamicTreeCut} | R Documentation

## Adaptive Branch Pruning of Hierarchical Clustering Dendrograms

### Description

This wrapper provides a common access point for two methods of adaptive branch pruning of hierarchical clustering dendrograms.

### Usage

    cutreeDynamic(
          dendro, cutHeight = NULL, minClusterSize = 20,

          # Basic tree cut options
          method = "hybrid", distM = NULL,
          deepSplit = (ifelse(method=="hybrid", 1, FALSE)),

          # Advanced options
          maxCoreScatter = NULL, minGap = NULL,
          maxAbsCoreScatter = NULL, minAbsGap = NULL,

          minSplitHeight = NULL, minAbsSplitHeight = NULL,

          # External (user-supplied) measure of branch split
          externalBranchSplitFnc = NULL, minExternalSplit = NULL,
          externalSplitOptions = list(),
          externalSplitFncNeedsDistance = NULL,
          assumeSimpleExternalSpecification = TRUE,

          # PAM stage options
          pamStage = TRUE, pamRespectsDendro = TRUE,
          useMedoids = FALSE, maxDistToLabel = NULL,
          maxPamDist = cutHeight,
          respectSmallClusters = TRUE,

          # Various options
          verbose = 2, indent = 0)

### Arguments

`dendro` | A hierarchical clustering dendorgram such as one returned by `hclust`.
`cutHeight` | Maximum joining heights that will be considered. For `method=="tree"` it defaults to 0.99. For `method=="hybrid"` it defaults to 99% of the range between the 5th percentile and the maximum of the joining heights on the dendrogram.
`minClusterSize` | Minimum cluster size.
`method` | Chooses the method to use. Recognized values are "hybrid" and "tree".
`distM` | Only used for method "hybrid". The distance matrix used as input to `hclust`. If not given and `method == "hybrid"`, the function will issue a warning and default to `method = "tree"`.
`deepSplit` | For method "hybrid", can be either logical or integer in the range 0 to 4. For method "tree", must be logical. In both cases, provides a rough control over sensitivity to cluster splitting. The higher the value (or if `TRUE`), the more and smaller clusters will be produced. For the "hybrid" method, a finer control can be achieved via `maxCoreScatter` and `minGap` below.
`maxCoreScatter` | Only used for method "hybrid". Maximum scatter of the core for a branch to be a cluster, given as the fraction of `cutHeight` relative to the 5th percentile of joining heights. See Details.
`minGap` | Only used for method "hybrid". Minimum cluster gap given as the fraction of the difference between `cutHeight` and the 5th percentile of joining heights.
`maxAbsCoreScatter` | Only used for method "hybrid". Maximum scatter of the core for a branch to be a cluster given as absolute heights. If given, overrides `maxCoreScatter`.
`minAbsGap` | Only used for method "hybrid". Minimum cluster gap given as absolute height difference. If given, overrides `minGap`.
`minSplitHeight` | Minimum split height given as the fraction of the difference between `cutHeight` and the 5th percentile of joining heights. Branches merging below this height will automatically be merged. Defaults to zero but is used only if `minAbsSplitHeight` below is `NULL`.
`minAbsSplitHeight` | Minimum split height given as an absolute height. Branches merging below this height will automatically be merged. If not given (default), will be determined from `minSplitHeight` above.
`externalBranchSplitFnc` | Optional function to evaluate split (dissimilarity) between two branches. Either a single function or a list in which each component is a function (see `assumeSimpleExternalSpecification` below for how to specify a single function). Each function can be specified by name (a character string) or the actual function object. Each given function must take arguments `branch1` and `branch2` that specify the indices of objects in the two branches whose dissimilarity is to be evaluated, and possibly other arguments. It must return a number that quantifies the dissimilarity of the two branches. The returned value will be compared to `minExternalSplit` (see below). This argument is only used for method "hybrid".
`minExternalSplit` | Thresholds to decide whether two branches should be merged. It should be a numeric vector of the same length as the number of functions in `externalBranchSplitFnc` above. Only used for method "hybrid".
`externalSplitOptions` | Further arguments to function `externalBranchSplitFnc`. If only one external function is specified in `externalBranchSplitFnc` above, `externalSplitOptions` can be a named list of arguments or a list with one component that is in turn the named list of further arguments for `externalBranchSplitFnc[[1]]`. The argument `assumeSimpleExternalSpecification` controls which of the two possibilities should be assumed. If multiple functions are specified in `externalBranchSplitFnc`, `externalSplitOptions` must be a list in which each component is a named list giving the further arguments for the corresponding function in `externalBranchSplitFnc`. Only used for method "hybrid".
`externalSplitFncNeedsDistance` | Optional specification of whether the external branch split functions need the distance matrix as one of their arguments. Either `NULL` or a logical vector with one element per branch split function that specifies whether the corresponding branch split function expects the distance matrix as one of its arguments. The default `NULL` is interpreted as a vector of `TRUE`. When dealing with a large number of objects, setting this argument to `FALSE` whenever possible can prevent unnecessary memory utilization.
`assumeSimpleExternalSpecification` | Logical: when `minExternalSplit` above is a scalar (has length 1), should the function assume a simple specification of `externalBranchSplitFnc` and `externalSplitOptions`? If `TRUE`, `externalBranchSplitFnc` is taken as the function specification and `externalSplitOptions` the named list of options. This is suitable for simple direct calls of this function. If `FALSE`, `externalBranchSplitFnc` is assumed to be a list with a single component which specifies the function, and `externalSplitOptions` is a list with one component that is in turn the named list of further arguments for `externalBranchSplitFnc[[1]]`.
`pamStage` | Only used for method "hybrid". If TRUE, the second (PAM-like) stage will be performed.
`pamRespectsDendro` | Logical, only used for method "hybrid". If `TRUE`, the PAM stage will respect the dendrogram in the sense that objects and small clusters will only be assigned to clusters that belong to the same branch that the objects or small clusters being assigned belong to.
`useMedoids` | Only used for method "hybrid" and only if `labelUnlabeled==TRUE`. If TRUE, the second stage will be use object to medoid distance; if FALSE, it will use average object to cluster distance. The default (FALSE) is recommended.
`maxDistToLabel` | Deprecated, use `maxPamDist` instead. Only used for method "hybrid" and only if `labelUnlabeled==TRUE`. Maximum object distance to closest cluster that will result in the object assigned to that cluster.
`maxPamDist` | Only used for method "hybrid" and only if `labelUnlabeled==TRUE`. Maximum object distance to closest cluster that will result in the object assigned to that cluster. Defaults to `cutHeight`.
`respectSmallClusters` | Only used for method "hybrid" and only if `labelUnlabeled==TRUE`. If TRUE, branches that failed to be clusters in stage 1 only because of insufficient size will be assigned together in stage 2. If FALSE, all objects will be assigned individually.
`verbose` | Controls the verbosity of the output. 0 will make the function completely quiet, values up to 4 gradually increase verbosity.
`indent` | Controls indentation of printed messages (see `verbose` above). Each unit adds two spaces before printed messages; useful when several functions' output is to be nested.

### Details

This is a wrapper for two related but different methods for cluster detection in hierarchical clustering dendrograms.

In order to make the shape parameters `maxCoreScatter` and `minGap` more universal, their values are interpreted relative to `cutHeight` and the 5th percetile of the merging heights (we arbitrarily chose the 5th percetile rather than the minimum for reasons of stability). Thus, the absolute maximum allowable core scatter is calculated as `maxCoreScatter * (cutHeight - refHeight) + refHeight` and the absolute minimum allowable gap as `minGap * (cutHeight - refHeight)`, where `refHeight` is the 5th percentile of the merging heights.

### Value

A vector of numerical labels giving assignment of objects to modules. Unassigned objects are labeled 0, the largest module has label 1, next largest 2 etc.

### Author(s)

Peter Langfelder, Peter.Langfelder@gmail.com

### References

Langfelder P, Zhang B, Horvath S, 2007. http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/BranchCutting

### See Also

`hclust`, `cutreeHybrid`, `cutreeDynamicTree`.

[Package dynamicTreeCut version 1.63-1 Index]