This function takes an object of class iCellR and finds optimal number of clusters and clusters the data.
iclust(
x = NULL,
dist.method = "euclidean",
sensitivity = 100,
data.type = "pca",
dims = 1:10,
return.graph = FALSE
)
An object of class iCellR.
An object of class iCellR.
the distance measure to be used to compute the dissimilarity matrix. This must be one of: "euclidean", "maximum", "mandatattan", "canberra", "binary", "minkowski" or "NULL". By default, distance="euclidean". If the distance is "NULL", the dissimilarity matrix (diss) should be given by the user. If distance is not "NULL", the dissimilarity matrix should be "NULL".
The higher the number the less sensitivity, default = 100.
Choose between "tsne", "pca", "umap", default = "pca".
PCA dimentions to be use for clustering, default = 1:10.
return igraph object, default = FALSE.