LSHTM_analysis/scripts/functions/lf_bp.R
2022-08-30 12:10:56 +01:00

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R

#############################
# Barplots: ggplot
# stats +/-
# violin +/-
# barplot +/
# beeswarm
#############################
lf_bp <- function(lf_df = lf_duet
, p_title = "DUET-DDG"
, colour_categ = "outcome"
, x_grp = "mutation_info_labels"
, y_var = "param_value"
, facet_var = "param_type"
, n_facet_row = 1
, y_scales = "free_y"
, colour_bp_strip = "khaki2"
, dot_size = 3
, dot_transparency = 0.3
, violin_quantiles = c(0.25, 0.5, 0.75) # can be NULL
, my_ats = 11 # axis text size
, my_als = 10 # axis label size
, my_fls = 10 # facet label size
, my_pts = 11 # plot title size)
, make_boxplot = FALSE
, bp_width = c("auto", 0.5)
, add_stats = TRUE
, stat_grp_comp = c("R", "S")
, stat_method = "wilcox.test"
, my_paired = FALSE
, stat_label = c("p.format", "p.signif")
) {
fwv = as.formula(paste0("~", facet_var))
#fwv = reformulate(facet_var)
p1 <- ggplot(lf_df, aes_string(x = x_grp, y = y_var)) +
facet_wrap( fwv
, nrow = n_facet_row
, scales = y_scales) +
geom_violin(trim = T
, scale = "width"
#, position = position_dodge(width = 0.9)
, draw_quantiles = violin_quantiles)
if (make_boxplot){
if (bp_width == "auto"){
bp_width = 0.5/length(unique(lf_df[[x_grp]]))
cat("\nAutomatically calculated boxplot width, using bp_width:\n", bp_width, "\n")
}else{
cat("\nBoxplot width value provided, using:", bp_width, "\n")
bp_width = bp_width}
p2 = p1 + geom_boxplot(fill = "white"
, outlier.colour = NA
#, position = position_dodge(width = 0.9)
, width = bp_width) +
geom_quasirandom(#priority = "density"
#, shape = 21
size = dot_size
, alpha = dot_transparency
, show.legend = FALSE
, cex = 0.8
, aes(
colour = factor(
eval(
parse(
text = colour_categ
)
)
)
)
) + ggplot2::scale_color_manual(values = consurf_colours)
} else {
#Legend=factor(eval(parse(text = colour_categ)))
# ggbeeswarm (better than geom_point)
p2 = p1 +
#theme(legend.title=element_text('XXX')) + # Legend doesn't need a title)
geom_quasirandom(#priority = "density"
#, shape = 21
size = dot_size
, alpha = dot_transparency
, show.legend = FALSE
# , fast = FALSE
, cex = 0.8
, aes(
colour = factor(
eval(
parse(
text = colour_categ
)
)
)
)
#, aes(colour = Legend)
) +
ggplot2::scale_color_manual(values = consurf_colours)
}
# Add foramtting to graph
OutPlot = p2 + theme(axis.text.x = element_text(size = my_ats)
, axis.text.y = element_text(size = my_ats
, angle = 0
, hjust = 1
, vjust = 0)
, axis.title.x = element_text(size = my_ats)
, axis.title.y = element_text(size = my_ats)
, plot.title = element_text(size = my_pts
, hjust = 0.5
, colour = "black"
, face = "bold")
, strip.background = element_rect(fill = colour_bp_strip)
, strip.text.x = element_text(size = my_fls
, colour = "black")
, legend.title = element_text(color = "black"
, size = my_als)
, legend.text = element_text(size = my_ats)
, legend.direction = "vertical") +
labs(title = p_title
, x = ""
, y = "")
if (add_stats){
my_comparisonsL <- list( stat_grp_comp )
OutPlot = OutPlot + stat_compare_means(comparisons = my_comparisonsL
, method = stat_method
, paired = my_paired
, label = stat_label[2])
return(OutPlot)
}
return(OutPlot)
}