R: Clustering Method Stability Facet Plot

plot_clustering_difference_facet {ClustAssess} | R Documentation

## Clustering Method Stability Facet Plot

### Description

Display the distribution of the EC consistency for each clustering method and each resolution value on a given embedding The 'all' field of the object returned by the 'get_clustering_difference_object' method is used.

### Usage

    plot_clustering_difference_facet(
      clustering_difference_object,
      embedding,
      low_limit = 0,
      high_limit = 1,
      grid = TRUE
    )

### Arguments

`clustering_difference_object` | An object returned by the 'get_clustering_difference_object' method.
`embedding` | An embedding (only the first two dimensions will be used for visualisation).
`low_limit` | The lowest value of ECC that will be displayed on the embedding.
`high_limit` | The highest value of ECC that will be displayed on the embedding.
`grid` | Boolean value indicating whether the facet should be a grid (where each row is associated with a resolution value and each column with a clustering method) or a wrap.

### Value

A ggplot2 object.

### Examples

    set.seed(2021)
    # create an artificial expression matrix
    expr_matrix = matrix(c(runif(250*10), runif(250*10, min = 5, max = 7)), nrow = 500)
    rownames(expr_matrix) = as.character(1:500)

    pca_embedding = irlba::irlba(expr_matrix, nv = 2)
    pca_embedding = pca_embedding$u %*% diag(pca_embedding$d)
    rownames(pca_embedding) = as.character(1:500)

    adj_matrix = Seurat::FindNeighbors(pca_embedding,
        k.param = 10,
        nn.method = "rann",
        verbose = FALSE,
        compute.SNN = FALSE)$nn
    clust_diff_obj = get_clustering_difference(graph_adjacency_matrix = adj_matrix,
        resolution = c(0.5, 1),
        n_repetitions = 10,
        algorithm = 1:2,
        verbose = FALSE)
    plot_clustering_difference_facet(clust_diff_obj,pca_embedding)

[Package ClustAssess version 0.3.0 Index]