consensus_clustering_scExp {ChromSCape} | R Documentation

## Wrapper to apply ConsensusClusterPlus to scExp object

### Description

Runs consensus hierarchical clustering on PCA feature space of scExp object. Plot consensus scores for each number of clusters. See ConsensusClusterPlus - Wilkerson, M.D., Hayes, D.N. (2010). ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics, 2010 Jun 15;26(12):1572-3.

### Usage

    consensus_clustering_scExp(
      scExp,
      prefix = NULL,
      maxK = 10,
      reps = 100,
      pItem = 0.8,
      pFeature = 1,
      distance = "pearson",
      clusterAlg = "hc",
      innerLinkage = "ward.D",
      finalLinkage = "ward.D",
      plot_consclust = "pdf",
      plot_icl = "png"
    )

### Arguments

`scExp` | A SingleCellExperiment object containing 'PCA' in reducedDims.
`prefix` | character value for output directory. Directory is created only if plot_consclust is not NULL. This title can be an abosulte or relative path.
`maxK` | integer value. maximum cluster number to evaluate. (10)
`reps` | integer value. number of subsamples. (100)
`pItem` | numerical value. proportion of items to sample. (0.8)
`pFeature` | numerical value. proportion of features to sample. (1)
`distance` | character value. 'pearson': (1 - Pearson correlation), 'spearman' (1 - Spearman correlation), 'euclidean', 'binary', 'maximum', 'canberra', 'minkowski' or custom distance function. ('pearson')
`clusterAlg` | character value. cluster algorithm. 'hc' heirarchical (hclust), 'pam' for paritioning around medoids, 'km' for k-means upon data matrix, 'kmdist' ('hc') for k-means upon distance matrices (former km option), or a function that returns a clustering. ('hc')
`innerLinkage` | hierarchical linkage method for subsampling. ('ward.D')
`finalLinkage` | hierarchical linkage method for consensus matrix. ('ward.D')
`plot_consclust` | character value. NULL - print to screen, 'pdf', 'png', 'pngBMP' for bitmap png, helpful for large datasets. ('pdf')
`plot_icl` | same as above for item consensus plot. ('png')

### Details

This functions takes as input a SingleCellExperiment object that must have 'PCA' in reducedDims and outputs a SingleCellExperiment object containing consclust list calculated cluster consensus and item consensus scores in metadata.

### Value

Returns a SingleCellExperiment object containing consclust list, calculated cluster consensus and item consensus scores in metadata.

### References

ConsensusClusterPlus package by Wilkerson, M.D., Hayes, D.N. (2010). ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics, 2010 Jun 15;26(12):1572-3.

### Examples

    data("scExp")
    scExp_cf = correlation_and_hierarchical_clust_scExp(scExp)
    scExp_cf = consensus_clustering_scExp(scExp)

[Package ChromSCape version 1.2.62 Index]