Plot best calls for each cluster on a tSNE or umap

Usage

plot_best_call(
  cor_mat,
  metadata,
  cluster_col = "cluster",
  collapse_to_cluster = FALSE,
  threshold = 0,
  x = "UMAP_1",
  y = "UMAP_2",
  plot_r = FALSE,
  per_cell = FALSE,
  ...
)

Arguments

cor_mat: input similarity matrix
metadata: input metadata with tsne or umap coordinates and cluster ids
cluster_col: metadata column, can be cluster or cellid
collapse_to_cluster: if a column name is provided, takes the most frequent call of entire cluster to color in plot
threshold: minimum correlation coefficent cutoff for calling clusters
x: x variable
y: y variable
plot_r: whether to include second plot of cor eff for best call
per_cell: whether the cor_mat was generate per cell or per cluster
...: passed to plot_dims

Value

ggplot object, cells projected by dr, colored by cell type classification

Examples

res <- clustify(
    input = pbmc_matrix_small,
    metadata = pbmc_meta,
    ref_mat = cbmc_ref,
    query_genes = pbmc_vargenes,
    cluster_col = "classified"
)
#> using # of genes: 599
#> similarity computation completed, matrix of 9 x 13, preparing output

plot_best_call(
    cor_mat = res,
    metadata = pbmc_meta,
    cluster_col = "classified"
)