R/AS_dotplot.R
In CHKim5/LMSstat: AUTOMATION OF STATISTICAL TESTS WITH AN IDENTICAL DATA INPUT.
Defines functions
AS_dotplot
Documented in
AS_dotplot
#' Automatically save dotplots for all metabolites including asterisks for significance.
#'
#' @param data List inheriting from Allstats
#' @param asterisk Choose asterisk to plot ("Dunn","Scheffe","u_test","t_test")
#' @param significant_variable_only show significant variable only (T,F)
#' @param color colors used for ggplots.
#' @param order order of the groups; order = c("A","B","C")
#' @param legend_position legend position "none","left","right","bottom","top"
#' @param tip_length significance tip length
#' @param label_size significance label size
#' @param step_increase significance step increase
#' @param size dot size
#' @param fig_width figure size
#' @param fig_height figure size
#' @param Y_text Y axis title size
#' @param X_text X axis text size
#' @param Y_lab y axis text size
#' @param T_size Title size
#' @param sig_int significance parameter
#'
#' @return ggdotplot
#' @export
#'
#' @examples data(Data)
#' Test<-Allstats(Data)
#' AS_dotplot(Test,asterisk = "Dunn",significant_variable_only = F,color = c("#FF3300","#FF6600","#FFCC00","#99CC00","#0066CC","#660099") )
AS_dotplot<-function(data,
asterisk="t_test",
significant_variable_only=F,
color=c("#FF3300","#FF6600","#FFCC00","#99CC00","#0066CC","#660099"),
legend_position = "none",
order = NULL,
tip_length = 0.01,
label_size = 2.88,
step_increase = 0.05,
size = NULL,
fig_width = NA,
fig_height = NA,
X_text = 10,
Y_text = 12,
Y_lab = 10,
T_size =15,
sig_int = c(0.05,0.01)){
{#Summary
###Plot_data_prep###
ifelse(!dir.exists(file.path(getwd(), "dotplot")), dir.create(file.path(getwd(), "dotplot")), FALSE)
data[["Data_renamed"]]<-data[["Data_renamed"]] %>% mutate(
ZZZZ =data[["Data_renamed"]][,2] )
data[["Data_renamed"]]<-data[["Data_renamed"]][,c(-1,-2)]
data[["Data_renamed"]][,1:(ncol(data[["Data_renamed"]])-1)]<-sapply(data[["Data_renamed"]][,1:(ncol(data[["Data_renamed"]])-1)],
function(x) as.numeric(x))
NAMES<-colnames(data[["Data"]][3:ncol(data[["Data"]])])
data[["Data_renamed"]]$ZZZZ<-as.factor(data[["Data_renamed"]]$ZZZZ)
colnames(data[["Data_renamed"]])[ncol(data[["Data_renamed"]])]<-"Group"
Comb<-gtools::combinations(length(unique(data[["Data"]]$Group)),2,unique(data[["Data"]]$Group))
ckey<-color[1:length(unique(data[["Data"]]$Group))]
if (asterisk =="Scheffe"){
p_val_data<-data[["Anova_PostHoc"]]}
else if (asterisk =="t_test"){
p_val_data<-data[["t_test"]]}
else if (asterisk =="u_test"){
p_val_data<-data[["u_test"]]}
else if (asterisk =="Dunn"){
p_val_data<-data[["Dunn"]]}
else {
print("Wrong asterisk input must be one of (Dunn,Scheffe,u_test,t_test)")}
if(length(unique(data[["Data"]]$Group)) !=2){
for(a in 1:nrow(p_val_data)){
for(b in 1:ncol(p_val_data)){
if(is.nan(p_val_data[a,b])==T){
p_val_data[a,b]<-1
}
}
}}
else if (length(unique(data[["Data"]]$Group))==2){
for(b in 1:length(p_val_data)){
if(is.nan(p_val_data[b])==T){
p_val_data[b]<-1
}
}
}
}
###Plots###
suppressWarnings(
if (length(unique(data[["Data_renamed"]][["Group"]]))!=2) {
for (number in 1:nrow(p_val_data)){
if (number == round(nrow(p_val_data)/4)){print("25% complete")}
if (number == round(nrow(p_val_data)/3)){print("33% complete")}
if (number == round(nrow(p_val_data)/2)){print("50% complete")}
if (number == round(2*nrow(p_val_data)/3)){print("66% complete")}
if (number == round(3*nrow(p_val_data)/4)){print("75% complete")}
if (number == nrow(p_val_data)){print("100% complete")}
stat.test <- as.data.frame(matrix(data = NA, nrow = nrow(Comb),
ncol = 2))
stat.test[, 1:2] <- Comb
if (asterisk == "Dunn"){
rownames(stat.test)<-paste0(stat.test[,1]," - ",stat.test[,2])}
else{
rownames(stat.test)<-paste0(stat.test[,1],"-",stat.test[,2])}
colnames(p_val_data)<-as.data.frame(strsplit(colnames(p_val_data),"___"))[1,]
t1<-as.data.frame(t(as.data.frame(p_val_data)[number,]))
t2<-stat.test
t3<-merge(t2,t1,by=0)
stat.test<-t3[,2:4]
colnames(stat.test) <- c("group1", "group2",
"p")
stat.test<-stat.test %>% plyr::mutate(
p.adj.signif = case_when(p >
sig_int[1] ~ "NS", p <= sig_int[1] & p > sig_int[2] ~ "*",
p <= sig_int[2] ~ "**")
)
stat.test<-stat.test[stat.test$p.adj.signif != "NS",]
if (length(stat.test>4)){
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)+
ggpubr::stat_pvalue_manual(stat.test,
y.position = 1.05 * max(data[["Data_renamed"]][,number]),
step.increase = step_increase,
label.size = label_size,
tip.length = tip_length,
label = "p.adj.signif",
size = 3.5,
vjust = 0.05)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)}
else if(significant_variable_only == F) {
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)}}}
else if (length(unique(data[["Data_renamed"]][["Group"]]))==2) {
p_val_data<-as.data.frame(p_val_data)
if (asterisk=="t_test"){
colnames(p_val_data)<-colnames(data[["Result"]])[1]
}
else if(asterisk == "u_test"){
colnames(p_val_data)<-colnames(data[["Result"]])[2]
}
for (number in 1:nrow(p_val_data)){
if (number == round(nrow(p_val_data)/4)){print("25% complete")}
if (number == round(nrow(p_val_data)/3)){print("33% complete")}
if (number == round(nrow(p_val_data)/2)){print("50% complete")}
if (number == round(2*nrow(p_val_data)/3)){print("66% complete")}
if (number == round(3*nrow(p_val_data)/4)){print("75% complete")}
if (number == nrow(p_val_data)){print("100% complete")}
df <- data_summary(data[["Data_renamed"]],
varname = colnames(data[["Data_renamed"]])[number],
groupnames = c("Group"))
df <- df %>% plyr::mutate(ymax = len + SEM)
colnames(df)[1] <- "Group"
stat.test <- as.data.frame(matrix(data = NA, nrow = nrow(Comb),
ncol = 2))
stat.test[, 1:2] <- Comb
if (asterisk == "Dunn") {
rownames(stat.test) <- paste0(stat.test[, 1],
" - ", stat.test[, 2])
}
else {
rownames(stat.test) <- paste0(stat.test[, 1],
"-", stat.test[, 2])
}
colnames(p_val_data) <- as.data.frame(strsplit(colnames(p_val_data),
"___"))[1, ]
t1 <- as.data.frame(t(as.data.frame(p_val_data[number,
])))
rownames(t1)<-colnames(p_val_data)
t2 <- stat.test
t3 <- merge(t2, t1, by = 0)
stat.test <- t3[, 2:4]
colnames(stat.test) <- c("group1", "group2",
"p")
stat.test <- stat.test %>% plyr::mutate(p.adj.signif = case_when(p >
sig_int[1] ~ "NS", p <= sig_int[1] & p > sig_int[2] ~ "*",
p <= sig_int[2] ~ "**"))
stat.test <- stat.test[stat.test$p.adj.signif !=
"NS", ]
if (length(stat.test>4)){
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)+
ggpubr::stat_pvalue_manual(stat.test,
y.position = 1.05 * max(data[["Data_renamed"]][,number]),
step.increase = step_increase,
label.size = label_size,
tip.length = tip_length,
label = "p.adj.signif",
size = 3.5,
vjust = 0.05)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)}
else if(significant_variable_only == F) {
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)
}
}}
)
}
CHKim5/LMSstat documentation built on Dec. 17, 2021, 12:55 p.m.
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Defines functions AS_dotplot
Documented in AS_dotplot
#' Automatically save dotplots for all metabolites including asterisks for significance.
#'
#' @param data List inheriting from Allstats
#' @param asterisk Choose asterisk to plot ("Dunn","Scheffe","u_test","t_test")
#' @param significant_variable_only show significant variable only (T,F)
#' @param color colors used for ggplots.
#' @param order order of the groups; order = c("A","B","C")
#' @param legend_position legend position "none","left","right","bottom","top"
#' @param tip_length significance tip length
#' @param label_size significance label size
#' @param step_increase significance step increase
#' @param size dot size
#' @param fig_width figure size
#' @param fig_height figure size
#' @param Y_text Y axis title size
#' @param X_text X axis text size
#' @param Y_lab y axis text size
#' @param T_size Title size
#' @param sig_int significance parameter
#'
#' @return ggdotplot
#' @export
#'
#' @examples data(Data)
#' Test<-Allstats(Data)
#' AS_dotplot(Test,asterisk = "Dunn",significant_variable_only = F,color = c("#FF3300","#FF6600","#FFCC00","#99CC00","#0066CC","#660099") )
AS_dotplot<-function(data,
asterisk="t_test",
significant_variable_only=F,
color=c("#FF3300","#FF6600","#FFCC00","#99CC00","#0066CC","#660099"),
legend_position = "none",
order = NULL,
tip_length = 0.01,
label_size = 2.88,
step_increase = 0.05,
size = NULL,
fig_width = NA,
fig_height = NA,
X_text = 10,
Y_text = 12,
Y_lab = 10,
T_size =15,
sig_int = c(0.05,0.01)){
{#Summary
###Plot_data_prep###
ifelse(!dir.exists(file.path(getwd(), "dotplot")), dir.create(file.path(getwd(), "dotplot")), FALSE)
data[["Data_renamed"]]<-data[["Data_renamed"]] %>% mutate(
ZZZZ =data[["Data_renamed"]][,2] )
data[["Data_renamed"]]<-data[["Data_renamed"]][,c(-1,-2)]
data[["Data_renamed"]][,1:(ncol(data[["Data_renamed"]])-1)]<-sapply(data[["Data_renamed"]][,1:(ncol(data[["Data_renamed"]])-1)],
function(x) as.numeric(x))
NAMES<-colnames(data[["Data"]][3:ncol(data[["Data"]])])
data[["Data_renamed"]]$ZZZZ<-as.factor(data[["Data_renamed"]]$ZZZZ)
colnames(data[["Data_renamed"]])[ncol(data[["Data_renamed"]])]<-"Group"
Comb<-gtools::combinations(length(unique(data[["Data"]]$Group)),2,unique(data[["Data"]]$Group))
ckey<-color[1:length(unique(data[["Data"]]$Group))]
if (asterisk =="Scheffe"){
p_val_data<-data[["Anova_PostHoc"]]}
else if (asterisk =="t_test"){
p_val_data<-data[["t_test"]]}
else if (asterisk =="u_test"){
p_val_data<-data[["u_test"]]}
else if (asterisk =="Dunn"){
p_val_data<-data[["Dunn"]]}
else {
print("Wrong asterisk input must be one of (Dunn,Scheffe,u_test,t_test)")}
if(length(unique(data[["Data"]]$Group)) !=2){
for(a in 1:nrow(p_val_data)){
for(b in 1:ncol(p_val_data)){
if(is.nan(p_val_data[a,b])==T){
p_val_data[a,b]<-1
}
}
}}
else if (length(unique(data[["Data"]]$Group))==2){
for(b in 1:length(p_val_data)){
if(is.nan(p_val_data[b])==T){
p_val_data[b]<-1
}
}
}
}
###Plots###
suppressWarnings(
if (length(unique(data[["Data_renamed"]][["Group"]]))!=2) {
for (number in 1:nrow(p_val_data)){
if (number == round(nrow(p_val_data)/4)){print("25% complete")}
if (number == round(nrow(p_val_data)/3)){print("33% complete")}
if (number == round(nrow(p_val_data)/2)){print("50% complete")}
if (number == round(2*nrow(p_val_data)/3)){print("66% complete")}
if (number == round(3*nrow(p_val_data)/4)){print("75% complete")}
if (number == nrow(p_val_data)){print("100% complete")}
stat.test <- as.data.frame(matrix(data = NA, nrow = nrow(Comb),
ncol = 2))
stat.test[, 1:2] <- Comb
if (asterisk == "Dunn"){
rownames(stat.test)<-paste0(stat.test[,1]," - ",stat.test[,2])}
else{
rownames(stat.test)<-paste0(stat.test[,1],"-",stat.test[,2])}
colnames(p_val_data)<-as.data.frame(strsplit(colnames(p_val_data),"___"))[1,]
t1<-as.data.frame(t(as.data.frame(p_val_data)[number,]))
t2<-stat.test
t3<-merge(t2,t1,by=0)
stat.test<-t3[,2:4]
colnames(stat.test) <- c("group1", "group2",
"p")
stat.test<-stat.test %>% plyr::mutate(
p.adj.signif = case_when(p >
sig_int[1] ~ "NS", p <= sig_int[1] & p > sig_int[2] ~ "*",
p <= sig_int[2] ~ "**")
)
stat.test<-stat.test[stat.test$p.adj.signif != "NS",]
if (length(stat.test>4)){
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)+
ggpubr::stat_pvalue_manual(stat.test,
y.position = 1.05 * max(data[["Data_renamed"]][,number]),
step.increase = step_increase,
label.size = label_size,
tip.length = tip_length,
label = "p.adj.signif",
size = 3.5,
vjust = 0.05)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)}
else if(significant_variable_only == F) {
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)}}}
else if (length(unique(data[["Data_renamed"]][["Group"]]))==2) {
p_val_data<-as.data.frame(p_val_data)
if (asterisk=="t_test"){
colnames(p_val_data)<-colnames(data[["Result"]])[1]
}
else if(asterisk == "u_test"){
colnames(p_val_data)<-colnames(data[["Result"]])[2]
}
for (number in 1:nrow(p_val_data)){
if (number == round(nrow(p_val_data)/4)){print("25% complete")}
if (number == round(nrow(p_val_data)/3)){print("33% complete")}
if (number == round(nrow(p_val_data)/2)){print("50% complete")}
if (number == round(2*nrow(p_val_data)/3)){print("66% complete")}
if (number == round(3*nrow(p_val_data)/4)){print("75% complete")}
if (number == nrow(p_val_data)){print("100% complete")}
df <- data_summary(data[["Data_renamed"]],
varname = colnames(data[["Data_renamed"]])[number],
groupnames = c("Group"))
df <- df %>% plyr::mutate(ymax = len + SEM)
colnames(df)[1] <- "Group"
stat.test <- as.data.frame(matrix(data = NA, nrow = nrow(Comb),
ncol = 2))
stat.test[, 1:2] <- Comb
if (asterisk == "Dunn") {
rownames(stat.test) <- paste0(stat.test[, 1],
" - ", stat.test[, 2])
}
else {
rownames(stat.test) <- paste0(stat.test[, 1],
"-", stat.test[, 2])
}
colnames(p_val_data) <- as.data.frame(strsplit(colnames(p_val_data),
"___"))[1, ]
t1 <- as.data.frame(t(as.data.frame(p_val_data[number,
])))
rownames(t1)<-colnames(p_val_data)
t2 <- stat.test
t3 <- merge(t2, t1, by = 0)
stat.test <- t3[, 2:4]
colnames(stat.test) <- c("group1", "group2",
"p")
stat.test <- stat.test %>% plyr::mutate(p.adj.signif = case_when(p >
sig_int[1] ~ "NS", p <= sig_int[1] & p > sig_int[2] ~ "*",
p <= sig_int[2] ~ "**"))
stat.test <- stat.test[stat.test$p.adj.signif !=
"NS", ]
if (length(stat.test>4)){
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)+
ggpubr::stat_pvalue_manual(stat.test,
y.position = 1.05 * max(data[["Data_renamed"]][,number]),
step.increase = step_increase,
label.size = label_size,
tip.length = tip_length,
label = "p.adj.signif",
size = 3.5,
vjust = 0.05)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)}
else if(significant_variable_only == F) {
ggpubr::ggstripchart(data[["Data_renamed"]],
x = "Group",
y = colnames(data[["Data_renamed"]])[number],
color = "Group",
palette = ckey,
order = order,
size = size)+
ggplot2::stat_summary(fun.y = median, fun.ymin = median, fun.ymax = median,
geom = "crossbar", width = 0.4,color="Black",size=0.2)+
ggplot2::scale_y_continuous(label=ecoflux::scientific_10x)+
ggplot2::labs(title=NAMES[number],x =NULL, y = "Intensity")+
ggplot2::theme_classic()+ ggplot2::theme(plot.title=ggplot2::element_text(size=T_size,
face="bold",
color="Black",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=ggplot2::element_text(size=15,
hjust=0.5), # subtitle
plot.caption=ggplot2::element_text(size=15), # caption
axis.title.x=ggplot2::element_text(vjust=10,
size=15), # X axis title
axis.title.y=ggplot2::element_text(size=Y_text), # Y axis title
axis.text.x=ggplot2::element_text(size=X_text,
vjust=.5), # X axis text
axis.text.y=ggplot2::element_text(size=Y_lab),
legend.position = legend_position)
ggplot2::ggsave(filename = paste(NAMES[number],"dotplot.png",collapse = ""),
path=paste0(getwd(),"/dotplot"),
width = fig_width,
height = fig_height)
}
}}
)
}
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