Description Usage Arguments Value
Takes ExpressionSet object and clusters the samples using hierarchical, k-means, or pam clustering.
1 2 | clusterCells(cellData, k = 3, methods = c("hierarchical", "kmeans", "pam"),
hier_dist = "euclidean", hier_clust = "ward")
|
cellData |
ExpressionSet object created with readCells (and preferably transformed with prepCells). It is also helpful to first run reduceGenes_var and reduceGenes_pca. |
k |
The number of desired clusters into which the samples are to be grouped. The function calcGap can be used to obtain an unbiased estimate of the number of clusters. |
methods |
Vector of character strings specifying which of the three clustering methods to perform. All three can be specified, or a subset of the three. |
hier_dist |
Character string specifying how to compute the distance matrix for 'hierarchical.' Equivalent to the 'method' parameter within the dist function. |
hier_clust |
Character string specifying the clustering method for 'hierarchical.' Equivalent to the 'method' parameter within the hclust function. |
For each clustering method specified, a column is added to pData containing the cluster information for each sample (clusters are designated by roman numerals).
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