R/show_sig_feature_corrplot.R
show_sig_feature_corrplot.Rd
This function is for association visualization. Of note,
the parameters p_val
and drop
will affect the visualization
of association results under p value threshold.
show_sig_feature_corrplot( tidy_cor, feature_list, sort_features = FALSE, sig_orders = NULL, drop = TRUE, return_plotlist = FALSE, p_val = 0.05, xlab = "Signatures", ylab = "Features", co_gradient_colors = scale_color_gradient2(low = "blue", mid = "white", high = "red", midpoint = 0), ca_gradient_colors = co_gradient_colors, plot_ratio = "auto", breaks_count = NULL )
tidy_cor | data returned by get_tidy_association. |
---|---|
feature_list | a character vector contains features want to be plotted. If missing, all features will be used. |
sort_features | default is |
sig_orders | signature levels for ordering. |
drop | if |
return_plotlist | if |
p_val | p value threshold. If p value larger than this threshold, the result becomes blank white. |
xlab | label for x axis. |
ylab | label for y axis. |
co_gradient_colors | a Scale object representing gradient colors used to plot for continuous features. |
ca_gradient_colors | a Scale object representing gradient colors used to plot for categorical features. |
plot_ratio | a length-2 numeric vector to set the height/width ratio. |
breaks_count | breaks for sample count. If set it to |
a ggplot2
object
# The data is generated from Wang, Shixiang et al. load(system.file("extdata", "asso_data.RData", package = "sigminer", mustWork = TRUE )) p <- show_sig_feature_corrplot( tidy_data.seqz.feature, p_val = 0.05, breaks_count = c(0L,200L, 400L, 600L, 800L, 1020L)) p