subClusterCells
¶
subClusterCells
Description¶
subcluster cells
Usage¶
subClusterCells(
gobject,
name = "sub_clus",
cluster_method = c("leiden", "louvain_community", "louvain_multinet"),
cluster_column = NULL,
selected_clusters = NULL,
hvg_param = list(reverse_log_scale = T, difference_in_cov = 1, expression_values =
"normalized"),
hvg_min_perc_cells = 5,
hvg_mean_expr_det = 1,
use_all_genes_as_hvg = FALSE,
min_nr_of_hvg = 5,
pca_param = list(expression_values = "normalized", scale_unit = T),
nn_param = list(dimensions_to_use = 1:20),
k_neighbors = 10,
resolution = 1,
n_iterations = 1000,
gamma = 1,
omega = 1,
python_path = NULL,
nn_network_to_use = "sNN",
network_name = "sNN.pca",
return_gobject = TRUE,
verbose = T
)
Arguments¶
Argument |
Description |
---|---|
|
giotto object |
|
name for new clustering result |
|
clustering method to use |
|
cluster column to subcluster |
|
only do subclustering on these clusters |
|
parameters for calculateHVG |
|
threshold for detection in min percentage of cells |
|
threshold for mean expression level in cells with detection |
|
forces all genes to be HVG and to be used as input for PCA |
|
minimum number of HVG, or all genes will be used as input for PCA |
|
parameters for runPCA |
|
parameters for parameters for createNearestNetwork |
|
number of k for createNearestNetwork |
|
resolution |
|
number of interations to run the Leiden algorithm. |
|
gamma |
|
omega |
|
specify specific path to python if required |
|
type of NN network to use (kNN vs sNN) |
|
name of NN network to use |
|
boolean: return giotto object (default = TRUE) |
|
verbose |
Details¶
- This function performs subclustering on selected clusters.
The systematic steps are:
subset Giotto object
identify highly variable genes
run PCA
create nearest neighbouring network
do clustering
Value¶
giotto object with new subclusters appended to cell metadata
Seealso¶
- ``doLouvainCluster_multinet` <#dolouvainclustermultinet>`_ , ``doLouvainCluster_community` <#dolouvainclustercommunity>`_
and @seealso ``doLeidenCluster` <#doleidencluster>`_