Merge clusters based on dendrogram

Description

Takes an input of hierarchical clusterings of clusters and returns estimates of number of proportion of non-null and merges those below a certain cutoff.

Usage

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## S4 method for signature 'matrix'
mergeClusters(x, cl, dendro = NULL,
  mergeMethod = c("none", "adjP", "locfdr", "MB", "JC"),
  plotType = c("none", "all", "mergeMethod", "adjP", "locfdr", "MB", "JC"),
  cutoff = 0.1, doPlot = TRUE, isCount = TRUE, ...)

## S4 method for signature 'ClusterExperiment'
mergeClusters(x, eraseOld = FALSE,
  isCount = FALSE, mergeMethod = "none", plotType = "all",
  clusterLabel = "mergeClusters", ...)

Arguments

x

data to perform the test on. It can be a matrix or a ClusterExperiment.

cl

A numeric vector with cluster assignments to compare to. “-1” indicates the sample was not assigned to a cluster.

dendro

dendrogram providing hierarchical clustering of clusters in cl; The default for matrix (NULL) is to recalculate it with the given (x, cl) pair. If x is a ClusterExperiment object, the dendrogram in the slot dendro_clusters will be used. This means that makeDendrogram needs to be called before mergeClusters.

mergeMethod

method for calculating proportion of non-null that will be used to merge clusters (if 'none', no merging will be done). See details for description of methods.

plotType

what type of plotting of dendrogram. If 'all', then all the estimates of proportion non-null will be plotted; if 'mergeMethod', then only the value used in the merging is plotted for each node.

cutoff

minimimum value required for NOT merging a cluster, i.e. two clusters with the proportion of DE below cutoff will be merged. Must be a value between 0, 1, where lower values will make it harder to merge clusters.

doPlot

logical as to whether to plot the dendrogram (overrides plotType value). Mainly used for internal coding purposes.

isCount

logical as to whether input data is a count matrix. See details.

...

for signature matrix, arguments passed to the plot.phylo function of ade4 that plots the dendrogram. For signature ClusterExperiment arguments passed to the method for signature matrix.

eraseOld

logical. Only relevant if input x is of class ClusterExperiment. If TRUE, will erase existing workflow results (clusterMany as well as mergeClusters and combineMany). If FALSE, existing workflow results will have "_i" added to the clusterTypes value, where i is one more than the largest such existing workflow clusterTypes.

clusterLabel

a string used to describe the type of clustering. By default it is equal to "mergeClusters", to indicate that this clustering is the result of a call to mergeClusters.

Details

If isCount=TRUE, and the input is a matrix, log2(count + 1) will be used for makeDendrogram and the original data with voom correction will be used in getBestFeatures). If input is ClusterExperiment, then setting isCount=TRUE also means that the log2(1+count) will be used as the transformation, like for the matrix case as well as the voom calculation, and will NOT use the transformation stored in the object. If FALSE, then transform(x) will be given to the input and will be used for both makeDendrogram and getBestFeatures, with no voom correction.

"JC" refers to the method of Ji and Cai (2007), and implementation of "JC" method is copied from code available on Jiashin Ji's website, December 16, 2015 (http://www.stat.cmu.edu/~jiashun/Research/software/NullandProp/). "locfdr" refers to the method of Efron (2004) and is implemented in the package locfdr. "MB" refers to the method of Meinshausen and Buhlmann (2005) and is implemented in the package howmany. "adjP" refers to the proportion of genes that are found significant based on a FDR adjusted p-values (method "BH") and a cutoff of 0.05.

If mergeMethod is not equal to 'none' then the plotting will indicate where the clusters will be merged (assuming plotType is not 'none').

Value

If 'x' is a matrix, it returns (invisibly) a list with elements

  • clustering a vector of length equal to ncol(x) giving the integer-valued cluster ids for each sample. "-1" indicates the sample was not clustered.

  • oldClToNew A table of the old cluster labels to the new cluster labels.

  • propDE A table of the proportions that are DE on each node.

  • originalClusterDendro The dendrogram on which the merging was based (based on the original clustering).

If 'x' is a ClusterExperiment, it returns a new ClusterExperiment object with an additional clustering based on the merging. This becomes the new primary clustering.

Examples

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data(simData)

#create a clustering, for 8 clusters (truth was 3)
cl<-clusterSingle(simData, clusterFunction="pam", subsample=FALSE,
sequential=FALSE, clusterDArgs=list(k=8))

#make dendrogram
cl <- makeDendrogram(cl)

#merge clusters with plotting. Note argument 'use.edge.length' can improve
#readability
merged <- mergeClusters(cl, plot=TRUE, plotType="all",
mergeMethod="adjP", use.edge.length=FALSE)

#compare merged to original
table(primaryCluster(cl), primaryCluster(merged))