multiSilhouette: Evaluate silhouette indices of clustered single cell data...

In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.

Evaluate silhouette indices of clustered single cell data across several cluster resolutions.

Description

Evaluate silhouette indices of clustered single cell data across several cluster resolutions. Consider running multiCluster(...) first.

Usage

multiSilhouette(
  object,
  groups,
  assay_pattern = NULL,
  assay = NULL,
  verbose = T
)

Arguments

object	Seurat object with multi-resolution clusters provided in meta data.
groups	Vector specifying names of all cluster configurations found in meta data.
assay_pattern	Cluster naming prefix.
assay	Seurat assay used for clustering. If not specified, default assay is used.
verbose	Print progress. Default is TRUE.

Value

Seurat object

Author(s)

Nicholas Mikolajewicz

See Also

multiCluster

Examples

msil_list <- multiSilhouette(object = so.query, groups = cluster.name, assay_pattern = assay.pattern, verbose = T)
sil.plot <- msil_list$silhouette_plots
plt.silw.dep <- msil_list$resolution_plot
df.silw <- msil_list$silhouette_raw
df.silw.sum <- msil_list$silhouette_summary
rm(msil_list); invisible({gc()})

NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.