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

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

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

See also

multiCluster

Author

Nicholas Mikolajewicz

Examples

msil_list <- multiSilhouette(object = so.query, groups = cluster.name, assay_pattern = assay.pattern, verbose = T)
#> Error in multiSilhouette(object = so.query, groups = cluster.name, assay_pattern = assay.pattern,     verbose = T): object 'assay.pattern' not found
sil.plot <- msil_list$silhouette_plots
#> Error in eval(expr, envir, enclos): object 'msil_list' not found
plt.silw.dep <- msil_list$resolution_plot
#> Error in eval(expr, envir, enclos): object 'msil_list' not found
df.silw <- msil_list$silhouette_raw
#> Error in eval(expr, envir, enclos): object 'msil_list' not found
df.silw.sum <- msil_list$silhouette_summary
#> Error in eval(expr, envir, enclos): object 'msil_list' not found
rm(msil_list); invisible({gc()})
#> Warning: object 'msil_list' not found