get_clustering_kmeans_subplan: Get a subplan for k-means clustering.

In bioinfocz/scdrake: A pipeline for droplet-based single-cell RNA-seq data secondary analysis implemented in the drake Make-like toolkit for R language

Get a subplan for k-means clustering.

Description

Besides k-means for selected number of ks, there is also a best k algorithm.

Usage

get_clustering_kmeans_subplan(
  sce_target_name,
  dimred,
  cluster_kmeans_k_enabled,
  cluster_kmeans_k,
  cluster_kmeans_kbest_enabled,
  is_integration,
  plots_out_dir
)

Arguments

sce_target_name	A character scalar: name of target representing a SCE object that will be used for k-means clustering.
dimred	A character scalar: which reducedDim() to use for clustering.
cluster_kmeans_k_enabled, cluster_kmeans_kbest_enabled	A logical scalar: if FALSE, disable the selected clustering and set all corresponding targets to NULL.
cluster_kmeans_k	An integer vector: ks for k-means.
is_integration	A logical scalar: if TRUE, clustering results will be named as ⁠cluster_int_kmeans_<method>[_k<k>]⁠. If FALSE, they will be named as ⁠cluster_kmeans_<method>[_k<k>]⁠.
plots_out_dir	A character scalar: path to output directory to save plots (e.g. clustree::clustree()).

Value

drake::drake_plan()

bioinfocz/scdrake documentation built on Sept. 19, 2024, 4:43 p.m.