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velocity_freq_plots.R
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velocity_freq_plots.R
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library(readxl)
library(tidyr)
library(dplyr)
library(patchwork)
library(cowplot)
library(ggplot2)
options(warn=-1)
# Prepare data for first plot ----
ifts<-list()
for (i in 1:4){
iftx<-suppressMessages(read_xlsx("IFT_Velocity_IFT_frequency_edited.xlsx", sheet = i))
iftx<-iftx[-1,]
ift_long<-pivot_longer(iftx, everything(), names_to = "Genotype", values_to = "Speed1", values_drop_na = TRUE)
ifty<-suppressMessages(read_xlsx("IFT_Velocity_IFT_frequency_edited.xlsx", sheet = i, skip = 1))
ift_long_2<-pivot_longer(ifty, everything(), names_to = "Part", values_to = "Speed", values_drop_na = TRUE)
ift_all<-cbind(ift_long, ift_long_2)
ift_all<-ift_all %>% select(-Speed1)
ift_all[,1:2]<-as.data.frame(lapply(ift_all[,1:2], function(x) gsub("\\.\\.\\.[0-9]+", "", x)))
ifts[[i]]<-ift_all
}
# First plot ----
plot1<-list()
for (i in 1:4){
iftplot<-ifts[[i]]
typelist<-unique(iftplot$Part)
genelist<-c("IFT-74::GFP","OSM-6::GFP","OSM-3::GFP","CHE-11::GFP")
iftplot$Part<-as.factor(iftplot$Part)
iftplot$Genotype<-factor(iftplot$Genotype, levels = unique(iftplot$Genotype))
do.call(patchwork::wrap_plots, c(lapply(typelist, function(a) {
ggplot(iftplot[iftplot$Part == a,], aes(x = Genotype, y = Speed, fill = Genotype)) +
geom_boxplot(outlier.shape = NA) +
scale_fill_manual(values=c("antiquewhite", "lightblue", "antiquewhite3", "antiquewhite4")) +
#scale_fill_brewer(palette="Accent") +
theme_classic() +
ylab("IFT Velocity") +
ggtitle(a) +
theme(legend.position = "right", text = element_text(family = "Open Sans SemiBold", size = 12),
plot.title = element_text(hjust = 0.6), axis.text.x=element_blank(), axis.title.x=element_blank())
}), nrow = 1, ncol = 3, guides = "collect")) -> plot
plot<-plot + plot_annotation(title = genelist[i], theme = theme(plot.title = element_text(hjust = 0.5)))
plot1[[i]]<-plot
}
plot_grid(plotlist = plot1, labels = "AUTO")
ggsave("ift_frequency.jpg", width = 30, height = 10, dpi = 300)
# Prepare data for 2nd plot ----
iftz<-suppressMessages(read_xlsx("IFT_Velocity_IFT_frequency_edited.xlsx", sheet = 5))
iftz<-iftz %>% select(!grep("number", as.character(as.vector(iftz[2,]))))
iftz<-iftz[c(-1,-2),]
iftz_long<-pivot_longer(iftz, everything(), names_to = "Genotype2", values_to = "Speed1", values_drop_na = TRUE)
iftz2<-suppressMessages(read_xlsx("IFT_Velocity_IFT_frequency_edited.xlsx", sheet = 5, skip = 1))
iftz2<-iftz2 %>% select(!grep("number", as.character(as.vector(iftz2[1,]))))
iftz2<-iftz2[-1,]
iftz_long_2<-pivot_longer(iftz2, everything(), names_to = "Genotype", values_to = "Speed2", values_drop_na = TRUE)
iftz3<-suppressMessages(read_xlsx("IFT_Velocity_IFT_frequency_edited.xlsx", sheet = 5, skip = 2))
iftz3<-iftz3 %>% select(!grep("number", colnames(iftz3)))
iftz_long_3<-pivot_longer(iftz3, everything(), names_to = "Part", values_to = "Speed", values_drop_na = TRUE)
iftz_all<-cbind(iftz_long, iftz_long_2, iftz_long_3)
iftz_all<-iftz_all %>% select(-Speed1, -Speed2)
iftz_all[,1:3]<-as.data.frame(lapply(iftz_all[,1:3], function(x) gsub("\\.\\.\\.[0-9]+", "", x)))
# 2nd plot ----
plot2<-list()
typelist2<-unique(iftz_all$Part)
genelist2<-unique(iftz_all$Genotype2)
for (i in 1:length(genelist2)){
iftplot2<-iftz_all[iftz_all$Genotype2 == genelist2[i],]
iftplot2$Genotype<-factor(iftplot2$Genotype, levels = unique(iftplot2$Genotype))
plot<-do.call(patchwork::wrap_plots, c(lapply(typelist2, function(a) {
ggplot(iftplot2[iftplot2$Part == a,], aes(x = Genotype, y = Speed, fill = Genotype)) +
geom_boxplot(outlier.shape = NA) +
scale_fill_manual(values=c("antiquewhite", "lightblue", "antiquewhite3", "antiquewhite4", "lightyellow", "yellow3")) +
#scale_fill_brewer(palette = "Accent") +
theme_classic()+
ylab("IFT Frequency") +
ggtitle(a) +
theme(legend.position = "right", text = element_text(family = "Open Sans SemiBold", size = 12),
plot.title = element_text(hjust = 0.6), axis.text.x=element_blank(), axis.title.x=element_blank())
}), nrow = 1, ncol = 3, guides = "collect")) +
plot_annotation(title = genelist2[i], theme = theme(plot.title = element_text(hjust = 0.5)))
plot2[[i]]<-plot
}
plot_grid(plotlist = plot2, labels = "AUTO")
ggsave("ift.jpg", width = 30, height = 10, dpi = 300)
ift2 <- ifts[[1]]
ift2$Marker <- "IFT-74::GFP"
for (i in 2:4) {
ift22 <- ifts[[i]]
genelist <- c("IFT-74::GFP", "OSM-6::GFP", "OSM-3::GFP", "CHE-11::GFP")
ift22$Marker <- genelist[i]
ift2 <- rbind(ift2, ift22)
}
colnames(ift2)[2:3] <- c("IFT", "Number.of.Particles")
# IFT
df <- ift2
df$IFT <- as.character(df$IFT)
df$Genotype <- as.character(df$Genotype)
df$Marker <- as.character(df$Marker)
Length <- "Number.of.Particles"
genotype <- "Genotype"
markers <- unique(df$Marker)
markers <- gsub(":", "", markers)
# Retrograde
types <- unique(df$IFT)
for (k in 1:length(types)) {
for (j in 1:length(markers)) {
dfx <- df %>%
filter(Marker == unique(df$Marker)[j] & IFT == types[k]) %>%
dplyr::select(Number.of.Particles, Genotype)
genelist <- unique(dfx[[genotype]])
x <- combn(genelist, 2)
y <- length(x) / 2
x1 <- parse_expr(genotype)
x2 <- parse_expr(Length)
m <- matrix("-", nrow = length(genelist), ncol = length(genelist))
ms <- matrix("-", nrow = length(genelist), ncol = length(genelist))
m <- matrix("-", nrow = length(genelist), ncol = length(genelist))
ms <- matrix("-", nrow = length(genelist), ncol = length(genelist))
for (i in 1:y) {
# print(c(x[1,i],x[2,i]))
# print(i)
s <- shapiro.test(dfx$Number.of.Particles[dfx[[genotype]] %in% c(x[1, i], x[2, i])])
if (s$p.value < 0.05) {
t <- wilcox.test(eval(x2) ~ eval(x1), data = dfx[dfx[[genotype]] %in% c(x[1, i], x[2, i]), ], exact = FALSE)
} else {
t <- t.test(eval(x2) ~ eval(x1), data = dfx[dfx[[genotype]] %in% c(x[1, i], x[2, i]), ], alternative = "two.sided", var.equal = FALSE)
}
m[which(genelist == x[1, i]), which(genelist == x[2, i])] <- as.numeric(t$p.value)
if (t$p.value < 0.05 && t$p.value >= 0.01) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "*"
} else if (t$p.value < 0.01 && t$p.value >= 0.001) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "**"
} else if (t$p.value < 0.001 && t$p.value >= 0.0001) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "***"
} else if (t$p.value < 0.0001) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "****"
} else {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "ns"
}
}
rownames(m) <- genelist
colnames(m) <- genelist
rownames(ms) <- genelist
colnames(ms) <- genelist
m <- t(m)
ms <- t(ms)
m <- as_tibble(m, rownames = NA)
ms <- as_tibble(ms, rownames = NA)
write.xlsx(m, paste0(types[k], "_velocity.xlsx"), sheetName = paste(markers[j]), append = TRUE)
write.xlsx(ms, paste0(types[k], "_velocity_sig.xlsx"), sheetName = paste(markers[j]), append = TRUE)
}
}
df2 <- iftz_all
colnames(df2) <- c("Marker", "Genotype", "IFT", "Number.of.Particles")
df2$IFT <- as.character(df2$IFT)
df2$Genotype <- as.character(df2$Genotype)
df2$Marker <- as.character(df2$Marker)
Length <- "Number.of.Particles"
genotype <- "Genotype"
markers <- unique(df2$Marker)
markers <- gsub(":", "", markers)
# Retrograde
types <- unique(df2$IFT)
for (k in 1:length(types)) {
for (j in 1:length(markers)) {
dfx <- df2 %>%
filter(Marker == unique(df2$Marker)[j] & IFT == types[k]) %>%
dplyr::select(Number.of.Particles, Genotype)
genelist <- unique(dfx[[genotype]])
x <- combn(genelist, 2)
y <- length(x) / 2
x1 <- parse_expr(genotype)
x2 <- parse_expr(Length)
m <- matrix("-", nrow = length(genelist), ncol = length(genelist))
ms <- matrix("-", nrow = length(genelist), ncol = length(genelist))
m <- matrix("-", nrow = length(genelist), ncol = length(genelist))
ms <- matrix("-", nrow = length(genelist), ncol = length(genelist))
for (i in 1:y) {
# print(c(x[1,i],x[2,i]))
# print(i)
s <- shapiro.test(dfx$Number.of.Particles[dfx[[genotype]] %in% c(x[1, i], x[2, i])])
if (s$p.value < 0.05) {
t <- wilcox.test(eval(x2) ~ eval(x1), data = dfx[dfx[[genotype]] %in% c(x[1, i], x[2, i]), ], exact = FALSE)
} else {
t <- t.test(eval(x2) ~ eval(x1), data = dfx[dfx[[genotype]] %in% c(x[1, i], x[2, i]), ], alternative = "two.sided", var.equal = FALSE)
}
m[which(genelist == x[1, i]), which(genelist == x[2, i])] <- as.numeric(t$p.value)
if (t$p.value < 0.05 && t$p.value >= 0.01) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "*"
} else if (t$p.value < 0.01 && t$p.value >= 0.001) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "**"
} else if (t$p.value < 0.001 && t$p.value >= 0.0001) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "***"
} else if (t$p.value < 0.0001) {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "****"
} else {
ms[which(genelist == x[1, i]), which(genelist == x[2, i])] <- "ns"
}
}
rownames(m) <- genelist
colnames(m) <- genelist
rownames(ms) <- genelist
colnames(ms) <- genelist
m <- t(m)
ms <- t(ms)
m <- as_tibble(m, rownames = NA)
ms <- as_tibble(ms, rownames = NA)
write.xlsx(m, paste0(types[k], "_freq.xlsx"), sheetName = paste(markers[j]), append = TRUE)
write.xlsx(ms, paste0(types[k], "_freq_sig.xlsx"), sheetName = paste(markers[j]), append = TRUE)
}
}
# 3rd plot ----
plot3<-list()
typelist3<-unique(iftzn_all$Part)
genelist3<-unique(iftzn_all$Genotype2)
for (i in 1:length(genelist3)){
iftplot3<-iftzn_all[iftzn_all$Genotype2 == genelist3[i],]
iftplot3$Genotype<-factor(iftplot3$Genotype, levels = unique(iftplot3$Genotype))
plot<-do.call(patchwork::wrap_plots, c(lapply(typelist3, function(a) {
ggplot(iftplot3[iftplot3$Part == a,], aes(x = Genotype, y = Speed, fill = Genotype)) +
geom_boxplot(outlier.shape = NA) +
scale_fill_manual(values=c("antiquewhite", "lightblue", "antiquewhite3", "antiquewhite4", "lightyellow", "yellow3")) +
#scale_fill_brewer(palette = "Accent") +
theme_classic()+
ylab("IFT Frequency") +
ggtitle(a) +
theme(legend.position = "right", text = element_text(family = "Open Sans SemiBold", size = 12),
plot.title = element_text(hjust = 0.6), axis.text.x=element_blank(), axis.title.x=element_blank())
}), nrow = 1, ncol = 3, guides = "collect")) +
plot_annotation(title = genelist3[i], theme = theme(plot.title = element_text(hjust = 0.3)))
plot3[[i]]<-plot
}
plot_grid(plotlist = plot3, labels = "AUTO", nrow = 3)
ggsave("ift3.jpg", width = 30, height = 20, dpi = 300)