ClusterSet-class: ClusterSet-class

In dputhier/dbfmcl: The scigenex package (Single-Cell Informative GENe Explorer)

ClusterSet-class

Description

This class is a representation of a partitioning algorithm and is intented to store gene clusters.

Value

A ClusterSet object.

Slots

data

A matrix containing the filtered and partitioned data.

gene_clusters

A list contains the partitioned genes of the dataset. Each element of the list corresponds to a cluster, and contains the indices of the genes assigned to that cluster.

top_genes

A list contains the top genes from the gene clusters. Each element of the list corresponds to a cluster, and contains the indices of the genes assigned to that cluster ranked by their correlation value within their cluster.

gene_clusters_metadata

A list contains metadata related to the gene clusters such as the number of gene clusters, their ID, and the number of genes contained in each of them.

gene_cluster_annotations

A list contains the result obtained from the GO enrichment analysis of gene clusters.

cells_metadata

A list containing metadata related to the cell clusters such as the clustering results the number of cell clusters, their order, colors associated to each cluster,...

dbf_output

A list containing the intermediates outputs of the DBF function : dknn, simulated distances, critical distance and fdr values.

parameters

A list containing the parameter used. Each element of the list correspond to a parameter.

Examples

library(Seurat)
load_example_dataset("7871581/files/pbmc3k_medium")

# Select informative genes
res <- select_genes(pbmc3k_medium)
                    
# Cluster informative features
res <- gene_clustering(res, inflation=1.6)
is(res)

# Plot heatmap of gene clusters
plot_heatmap(res, row_labels = FALSE, line_size_horizontal = 2)
plot_heatmap(res[1,], row_labels = FALSE, line_size_horizontal = 2)
plot_heatmap(res[1:2, ], row_labels = FALSE, line_size_horizontal = 2)
plot_heatmap(res[1:2, 1:15], row_labels = FALSE, line_size_horizontal = 2)

# plot the profiles
idents <- Seurat::Idents(pbmc3k_medium)
plot_profiles(res,
              ident = idents)
             
# Some methods of the ClusterSet object
x <- ncol(res)
x <- nrow(res)
x <- dim(res)
x <- col_names(res)
x <- row_names(res)
x <- get_genes(res)
x<-  clust_size(res)
x <- c("IL32", "CCL5") %in% res
x <- which_clust(res, genes = c("IL32", "CCL5"))
res <- top_genes(res, top=5)
res <- res[2:3, ]
res <- rename_clust(res)
clust_names(res)
res <- res[, col_names(res)[1:10]]
show(res)    
show_methods(res)

dputhier/dbfmcl documentation built on May 31, 2024, 8:57 a.m.