Creates heatmap for genes within aggregated clusters.
plotMetaDataHeatmap( gobject, expression_values = c("normalized", "scaled", "custom"), metadata_cols = NULL, selected_genes = NULL, first_meta_col = NULL, second_meta_col = NULL, show_values = c("zscores", "original", "zscores_rescaled"), custom_cluster_order = NULL, clus_cor_method = "pearson", clus_cluster_method = "complete", custom_gene_order = NULL, gene_cor_method = "pearson", gene_cluster_method = "complete", gradient_color = c("blue", "white", "red"), gradient_midpoint = 0, gradient_limits = NULL, x_text_size = 10, x_text_angle = 45, y_text_size = 10, strip_text_size = 8, show_plot = NA, return_plot = NA, save_plot = NA, save_param = list(), default_save_name = "plotMetaDataHeatmap" )
gobject | giotto object |
---|---|
expression_values | expression values to use |
metadata_cols | annotation columns found in pDataDT(gobject) |
selected_genes | subset of genes to use |
first_meta_col | if more than 1 metadata column, select the x-axis factor |
second_meta_col | if more than 1 metadata column, select the facetting factor |
show_values | which values to show on heatmap |
custom_cluster_order | custom cluster order (default = NULL) |
clus_cor_method | correlation method for clusters |
clus_cluster_method | hierarchical cluster method for the clusters |
custom_gene_order | custom gene order (default = NULL) |
gene_cor_method | correlation method for genes |
gene_cluster_method | hierarchical cluster method for the genes |
gradient_color | vector with 3 colors for numeric data |
gradient_midpoint | midpoint for color gradient |
gradient_limits | vector with lower and upper limits |
x_text_size | size of x-axis text |
x_text_angle | angle of x-axis text |
y_text_size | size of y-axis text |
strip_text_size | size of strip text |
show_plot | show plot |
return_plot | return ggplot object |
save_plot | directly save the plot [boolean] |
save_param | list of saving parameters, see |
default_save_name | default save name |
ggplot or data.table
Creates heatmap for the average expression of selected genes in the different annotation/cluster groups. Calculation of cluster or gene order is done on the provided expression values, but visualization is by default on the z-scores. Other options are the original values or z-scores rescaled per gene (-1 to 1).
plotMetaDataCellsHeatmap
for numeric cell annotation instead of gene expression.
if (FALSE) { data(mini_giotto_single_cell) # get all genes all_genes = slot(mini_giotto_single_cell, 'gene_ID') # look at cell metadata cell_metadata = pDataDT(mini_giotto_single_cell) # plot heatmap per cell type, a column name from cell_metadata plotMetaDataHeatmap(mini_giotto_single_cell, selected_genes = all_genes[1:10], metadata_cols = 'cell_types') }