Cluster spacedeconv results
cluster.RdPerforms clustering on data obtained from a SpatialExperiment object using specified methods. This function allows for clustering based on deconvolution results, expression data, pathway, or transcription factors (TF) analyses.
Usage
cluster(
spe,
method = c("kmeans", "hclust"),
spmethod = c("expression", "progeny", "dorothea", "collectri",
unname(deconvolution_methods)),
dist_method = c("correlation", "euclidean", "maximum", "manhattan", "canberra",
"binary", "minkowski"),
hclust_method = c("complete", "ward.D", "ward.D2", "single", "average", "mcquitty",
"median", "centroid"),
nclusters = 3,
pca_dim = seq(1, 30),
clusres = 0.5,
...
)Arguments
- spe
A SpatialExperiment object containing the data to be clustered.
- method
A character vector specifying the clustering method to use. Options are "kmeans" and "hclust". Default is c("kmeans", "hclust").
- spmethod
A character vector indicating the type of analysis for clustering. Options include "expression", "progeny", "dorothea", "collectri", and names of deconvolution methods. Default is based on the available deconvolution methods.
- dist_method
A character vector specifying the distance measure to be used for "hclust" method. Options include "correlation", "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski".
- hclust_method
A character vector indicating the agglomeration method to be used with "hclust". Options include "complete", "ward.D", "ward.D2", "single", "average", "mcquitty", "median", "centroid".
- nclusters
An integer specifying the number of clusters to create. Default is 3.
- pca_dim
An integer vector specifying PCA dimensions to be used for clustering of expression data. This is used with Seurat::FindNeighbors. Default is seq(1, 30).
- clusres
A numeric value for the clustering resolution to be used with Seurat::FindClusters. Default is 0.5.
- ...
Additional parameters for clustering methods.