Description Usage Arguments Value Examples
View source: R/plot_pathway_heatmap.R
plot_pathway_heatmap() plots the results of output from the fgsea() function.
1 2 3 4 5 6 7 8 | plot_pathway_heatmap(path_table = NULL, path_res_df,
color_scale = c("blue", "lightyellow", "red"), cluster_row = T,
cluster_col = T, mark_sig = T, sig_para = "pval",
sigCutoff = 0.05, clustering_distance_rows = "euclidean",
clustering_method_rows = "complete",
clustering_distance_cols = "euclidean",
clustering_method_cols = "complete", flip_axes = F,
square_tiles = T)
|
path_table |
a dataframe of values |
path_res_df |
dataframe should contain columns "CellType", "pathway", "NES";can be output from the fgsea() function |
color_scale |
vector of colors to use for color scale; different options for color_scale_type requires different number of colors - "diverge" (3 colors), "seq" (2 colors), "rescale" (3 colors) |
mark_sig |
logical; whether to mark statistically significant results with a "*". |
sig_para |
parameter for statistical significance. |
sigCutoff |
cutoff for statistical significance. |
clustering_distance_rows |
distance measure used in clustering rows. Possible values are "correlation", "euclidean", "maximum", "manhattan", "canberra", "binary", or "minkowski" (defined in dist() function.) |
clustering_method_rows |
clustering method used for rows. Accepts the same values as hclust: "ward.D", "ward.D2", "single", "complete", "average" (=UPGMA), "mcquitty" (=WPGMA), "median" (=WPGMC) or "centroid" (=UPGMC). |
clustering_distance_cols |
distance measure used in clustering columns. Possible values are the same as clustering_distance_rows. |
clustering_method_cols |
clustering method used for columns. Accepts the same values as clustering_method_rows. |
flip_axes |
logical; if x- and y-axes should be flipped |
square_tiles |
logical; if tiles should made into squares |
cluster_rows |
logical; if rows should be clustered |
cluster_cols |
logical; if columns should be clustered |
A ggplot2 object
1 | plot_pathway_heatmap(path_table=NULL, path_res_df=my_pathway_enrichment)
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