plot_cor {clustifyr} | R Documentation |
Plot similarity measures on a tSNE or umap
plot_cor( cor_mat, metadata, data_to_plot = colnames(cor_mat), cluster_col = NULL, x = "UMAP_1", y = "UMAP_2", scale_legends = FALSE, ... )
cor_mat |
input similarity matrix |
metadata |
input metadata with per cell tsne or umap coordinates and cluster ids |
data_to_plot |
colname of data to plot, defaults to all |
cluster_col |
colname of clustering data in metadata, defaults to rownames of the metadata if not supplied. |
x |
metadata column name with 1st axis dimension. defaults to "UMAP_1". |
y |
metadata column name with 2nd axis dimension. defaults to "UMAP_2". |
scale_legends |
if TRUE scale all legends to maximum values in entire correlation matrix. if FALSE scale legends to maximum for each plot. A two-element numeric vector can also be passed to supply custom values i.e. c(0, 1) |
... |
passed to plot_dims |
list of ggplot objects, cells projected by dr, colored by cor values
res <- clustify( input = pbmc_matrix_small, metadata = pbmc_meta, ref_mat = cbmc_ref, query_genes = pbmc_vargenes, cluster_col = "classified" ) plot_cor( cor_mat = res, metadata = pbmc_meta, data_to_plot = colnames(res)[1:2], cluster_col = "classified", x = "UMAP_1", y = "UMAP_2" )