Plots heatmap showing activity scores for each activation mode

plot_heatmap_activity_mat(
  activity_mat,
  meta = NULL,
  annot_name = NULL,
  cluster_cols = T,
  cluster_rows = T,
  clustering_distance = "euclidean",
  clustering_method = "ward.D2",
  fontsize = 5,
  colors_annot = NULL,
  fontsize_row = 5,
  fontsize_col = 5
)

Arguments

activity_mat

Numeric matrix, containing activity for each activation mode of each pathway

meta

Dataframe containing metadata, with cell labels as rownames.

annot_name

Character, name of the column in meta that should be used to compute homogeneity for.

cluster_cols

Boolean, set to TRUE to perform column clustering.

cluster_rows

Boolean, set to TRUE to perform row clustering.

clustering_distance

Character, distance to use to perform clustering, one of "euclidean","correlation".

clustering_method

Character, one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).

fontsize

Integer, base fontsize for the plot.

colors_annot

Vector of colors to use.

Value

heatmap plot