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articletwo-ggplot.R
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articletwo-ggplot.R
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plot.alpha <- function(diversity,
alphabreaks = c(-Inf, -1, -0.1, -0.01, 0)) {
diversity <- diversity %>%
mutate(estimate = ifelse(response == "HYPERTENSION", log(alpha.effect), alpha.effect),
estimate_fac = cut(estimate, breaks = alphabreaks),
Qstar = ifelse(alpha.p < 0.05, '*', ' '))
plot.alpha.diversity <- ggplot(diversity, aes(x = reorder(Name, deseqplotorder(Name)),
y = 1,
fill = estimate_fac)) +
geom_bar(stat="identity", color="black") +
coord_flip() +
scale_fill_brewer(palette="Blues",
name = 'Regression coefficient \nin linear model \nfor Shannon index',
drop=FALSE,
direction = -1) +
theme_classic(20) +
geom_point(aes(Name, y=0.5, shape=Qstar), show.legend=FALSE, color='black', size=14) +
scale_shape_manual(name="",
values=c('*'='*', ' '=' '),
labels=c("*"="significant at\nFDR 0.05", ' '=' '),
breaks=c("*", ' ')) +
xlab("") +
ylab("") +
theme(legend.position="right",
legend.title=element_text(size = 14),
legend.direction="vertical",
legend.text=element_text(size = floor(0.75*20)),
legend.box.margin=margin(t = 0, unit = "cm"),
legend.margin=margin(0,0,0,0,"pt"),
legend.justification="left",
axis.line.y = element_line(linetype="blank"),
axis.line.x = element_line(linetype="blank"),
legend.title.align = 0,
legend.text.align = 0,
axis.text.y = element_text(color="black"),
axis.text.x = element_text(color="black"))+
scale_y_continuous(breaks=c(0.5), labels=c(expression(alpha)))
plot.alpha.diversity.gtable <- ggplot_gtable(ggplot_build(plot.alpha.diversity))
plot.alpha.diversity.legend <- legend_extractor(plot.alpha.diversity.gtable)
plot.alpha.diversity.yaxis <- plot.alpha.diversity.gtable$grobs[[3]]
plot.alpha.diversity <- plot.alpha.diversity +
theme(legend.position = "none",
axis.text.x = element_blank(),
axis.text.y=element_blank())
plot.gtable.alpha.diversity.stripped <- ggplot_gtable(ggplot_build(plot.alpha.diversity))
return(list(plot = plot.gtable.alpha.diversity.stripped$grobs[[6]],
yaxis = plot.alpha.diversity.yaxis,
xaxis = plot.alpha.diversity.gtable$grobs[[7]],
legend = plot.alpha.diversity.legend))
}
plot.beta <- function(diversity,
fig.textsize = 15,
ymax = 0.0016) {
diversity <- diversity %>% mutate(Qstar = ifelse(beta.p < 0.05, "*", "-"))
plot.beta.diversity <- ggplot(diversity,
aes(x = reorder(Name, deseqplotorder(Name)), y = beta.R2)) +
geom_bar(stat="identity", color = "black", fill = "gray96") +
geom_point(aes(y = beta.R2 - 0.00007, shape=Qstar), show.legend=FALSE, color='black', size=14) +
scale_shape_manual(values=c('*'='*', '-'='')) +
coord_flip() +
theme_classic(fig.textsize) +
ylab("Coefficient of determination for\nbeta diversity") +
scale_y_continuous(limits = c(0, ymax)) +
theme(legend.position="right",
legend.direction="vertical",
legend.box.margin=margin(0,0,0,0,"pt"),
legend.margin=margin(0,0,0,0,"pt"),
legend.justification="left",
legend.title.align = 0,
legend.text.align = 0)
plot.gtable.beta.diversity <- ggplot_gtable(ggplot_build(plot.beta.diversity))
plot.xlab.beta.diversity <- xlabb_extractor(plot.gtable.beta.diversity)
plot.beta.diversity <- plot.beta.diversity +
theme(axis.text.x = element_blank(),
axis.text.y = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
legend.position = "none")
plot.gtable.beta.diversity.stripped <- ggplot_gtable(ggplot_build(plot.beta.diversity))
return(list(plot = plot.gtable.beta.diversity.stripped$grobs[[6]],
xaxis = plot.gtable.beta.diversity$grobs[[7]],
xlab = plot.xlab.beta.diversity))
}
myforestplot <- function(data,
xlab = "",
ylab = "",
interceptone = FALSE,
subtitle = "",
my_y_scale = scale_y_continuous()) {
ggplot(data = data,
aes(x = term, y = estimate, ymin = conf.low, ymax = conf.high)) +
geom_point() +
{ if (interceptone) geom_hline(aes(fill=fake_salt), yintercept=1, linetype=2) } +
geom_errorbar(width=0.1)+
ggplot2::theme_minimal() +
theme(plot.title=element_text(size=16),
axis.title=element_text(size=10),
strip.background = element_blank()) +
theme(panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.x = element_line(),
axis.ticks.y = element_line(),
axis.line = element_line(colour = "black")) +
scale_x_discrete(labels=seq(3)) +
my_y_scale +
xlab(xlab) +
ylab(ylab) +
labs(subtitle = subtitle)
}
gvlma.table.plot <- function(model) {
{ sink("/dev/null");
gvlma.model <- gvlma::gvlma(model)
gvlma.modek.summary <- summary(gvlma.model)
; sink(); }
ret <- list("table" = gvlma.modek.summary,
"plot" = gvlma.model)
return(ret)
}
plot.diversities <- function(diversities) {
alpha.diversity.min <- plot.alpha(diversities$min, alphabreaks = seq(-1,0,0.2))
alpha.diversity.max <- plot.alpha(diversities$max, alphabreaks = seq(-1,0,0.2))
beta.diversity.min <- plot.beta(diversities$min)
beta.diversity.max <- plot.beta(diversities$max)
gs4 <- list(alpha.diversity.min$yaxis,
alpha.diversity.min$plot,
beta.diversity.min$plot,
alpha.diversity.min$legend,
alpha.diversity.min$xaxis,
beta.diversity.min$xaxis,
beta.diversity.min$xlab,
text_grob("Age- and sex-adjusted model", size = 18),
alpha.diversity.max$yaxis,
alpha.diversity.max$plot,
beta.diversity.max$plot,
alpha.diversity.max$xaxis,
beta.diversity.max$xaxis,
beta.diversity.max$xlab,
text_grob("Multivariable-adjusted model", size = 18))
g4 <- arrangeGrob(grobs = gs4,
layout_matrix = rbind(
c(8, 8, 8, NA, NA, NA, NA),
c(NA, 1, 2, NA, 3, NA, NA),
c(NA, 1, 2, NA, 3, NA, 4),
c(NA, NA, 5, NA,6, NA, NA),
c(NA, NA, NA, NA,7, NA, NA),
c(15, 15, 15, NA, NA, NA, NA),
c(NA, 9, 10, NA, 11, NA, NA),
c(NA, 9, 10, NA, 11, NA, NA),
c(NA, NA, 12, NA, 13, NA, NA),
c(NA, NA, NA, NA,14, NA, NA)),
widths=c(0.7, 4, 0.7, 0.1, 5, 0.7, 3),
heights=rep(c(1.5, 1, 6, 1, 2), 2))
return(g4)
}
deseqhaetmap <- function(df, legend.name = "Log Base Two\nFold Change") {
ggplot(df,
aes(x = reorder(Name, deseqplotorder(Name)),
y = ordered(Feature, levels=rev(unique(Feature))),
fill = log2FoldChange)) +
geom_tile(aes(fill = 1)) +
geom_tile(colour="white", size=0.25) +
scale_fill_distiller(palette = "RdBu",
name = legend.name,
limits=c(-1, 1),
breaks = c(-1, -0.5, 0.5, 0, 1),
na.value="grey30") +
xlab("") +
ylab("") +
theme_classic() +
theme(axis.text.x = element_text(angle=90, size=10, hjust=1.0,vjust=0.5),
axis.text.y = element_text(size=10),
legend.title = element_text(size=10),
legend.position = "right")
}
deseqplotorder <- function(x) {
y <- seq(length(x))
y[x == "Systolic BP"] = 0
y[x == "Diastolic BP"] = 1
y[x == "Pulse pressure"] = 2
y[x == "MAP"] = 3
y[x == "Hypertension"] = 4
y
}
saltplot <- function(dset, ymax = 2) {
ggplot(data = dset, aes(x = NA., y = g_Lactobacillus)) +
geom_point(aes(color = SEX), size = 0.05, position = "jitter") +
geom_smooth(method='lm', formula= y~x, colour = "black", size = 0.4) +
scale_x_continuous(limits=c(20, 205), expand = c(0, 0)) +
scale_y_log10(limits = c(100, 10000), expand = c(0, 0)) +
scale_colour_manual(name = "SEX",
labels = c("Male", "Female"),
breaks=c("0", "1"),
values = c("blue", "red")) +
xlab("24-hour urinary sodium [mmol]") +
ylab("Normalized Lactobacillus abundance count") +
guides(colour = guide_legend(override.aes = list(size=4, alpha = 0.4))) +
theme_classic() +
theme(plot.title = element_blank(),
legend.title = element_blank(),
legend.position = c(0.9,0.95))
}