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intestline_ms_figures.Rmd
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intestline_ms_figures.Rmd
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---
title: "Generating figures for intestline manuscript"
author: "Jiangyan Yu (jiangyan.yu@uni-bonn.de)"
date: "`r Sys.Date()`"
output:
html_document:
code_folding: hide
number_sections: yes
theme: united
toc: yes
toc_float: yes
pdf_document:
toc: yes
---
# library and directory
```{r}
rm(list=ls())
library(dplyr)
library(magrittr)
library(ggplot2)
## set working directory
working_dir = "/home/yu.j/sciebo/Projects/CODEX_ownerJY//"
figure_dir = paste0(working_dir,"/ms_figures")
##
intestline = read.csv(file = paste0(working_dir,"/CODEX_data/IntestLine-linear_structure_15-Sep-2022_09h27min.csv"))
base_layer = read.csv(file = paste0(working_dir,"/CODEX_data/better_backbone.csv"))
```
# fig2
## fig2b_selected_base_layer
```{r}
pdf(file = paste0(figure_dir,"/V2fig2b_selected_base_layer.pdf"),width = 8,height = 8)
plot(intestline$x,intestline$y,pch=16,cex=0.2,col="black")
points(base_layer$x,base_layer$y,pch=16,cex=0.5,col="red")
dev.off()
```
## fig2c_connect_spot_n_baselayer_after_filtering
```{r}
pdf(file = paste0(figure_dir,"/V2fig2c_connect_spot_n_baselayer_before_filtering.pdf"),width = 8,height = 8)
## select successfully projected spots
plot_data = subset(intestline,note == "Successfully projected")
plot(plot_data$x,plot_data$y,pch=16,cex=0)
segments(x0=plot_data$x,y0=plot_data$y,x1 = plot_data$nearest_Row, y1=plot_data$nearest_Column,pch=16,cex=0.1,lwd=0.1,col = "grey")
points(x=plot_data$nearest_Row,y=plot_data$nearest_Column,pch=16,cex=0.3,col="red")
dev.off()
```
## fig2d_filtering_distance
```{r}
pdf(file = paste0(figure_dir,"/V2fig2d_filtering_distance.pdf"),width = 4,height = 3)
plot.ecdf(x=intestline$Thickness,ylab = "Cumulative frequency",xlab="Distance to base layer",main = "")
abline(v = 1000, lty= 2, col = "red")
# title(main = "", xlab = "Distance to base layer")
dev.off()
```
## fig2e_filtering__zscore
```{r}
pdf(file = paste0(figure_dir,"/V2fig2e_filtering_zscore.pdf"),width = 4,height = 3)
## select successfully projected spots
plot_data = subset(intestline,note == "Successfully projected")
plot.ecdf(x=as.numeric(plot_data$zscore),ylab = "Cumulative frequency",xlab="Z-score of distances to the same base layer point",main = "")
abline(v = 2, lty= 2, col = "red")
# title(main = "", xlab = "Distance to base layer")
dev.off()
```
## fig2f_connect_spot_n_baselayer_after_filtering
```{r}
pdf(file = paste0(figure_dir,"/V2fig2f_connect_spot_n_baselayer_after_filtering.pdf"),width = 8,height = 8)
## select successfully projected spots
plot_data = subset(intestline,note == "Successfully projected")
## remove low noisy
plot_data = subset(plot_data, as.numeric(Thickness) < 1000 & as.numeric(zscore) <2)
plot(plot_data$x,plot_data$y,pch=16,cex=0)
segments(x0=plot_data$x,y0=plot_data$y,x1 = plot_data$nearest_Row, y1=plot_data$nearest_Column,pch=16,cex=0.1,lwd=0.1,col = "#457b9d")
points(x=plot_data$nearest_Row,y=plot_data$nearest_Column,pch=16,cex=0.3,col="red")
dev.off()
```
## fig2g_linear_structure
```{r}
pdf(file = paste0(figure_dir,"/V2fig2g_linear_structure.pdf"),width = 30,height = 4)
## select successfully projected spots
plot_data = subset(intestline,note == "Successfully projected")
## remove low noisy
plot_data = subset(plot_data, as.numeric(Thickness) < 1000 & as.numeric(zscore) <2)
plot(plot_data$Length,plot_data$Thickness,pch=16,cex=0.3,col = "#457b9d")
dev.off()
```
# fig3
## fig3a_rolled_image
```{r}
# markers = colnames(intestline)[18:34]
markers = c("Villin","Olfm4","Ki67","SMA","Lysozyme")
scale_marker = function(x){(x-min(x))/(max(x)-min(x))}
for(i in markers){
pdf(file = paste0(figure_dir,"/V2fig3a_rolled_",i,".pdf"),width = 8,height = 8)
# i = "Ki67"
tmp_data = intestline[,c("x","y",i)]
tmp_data$scaled = scale_marker(intestline[,i])
tmp_data = tmp_data[order(tmp_data[, "scaled"],decreasing = FALSE),]
p = ggplot(tmp_data,aes(x,y,color=scaled))+
geom_point(size=0.01)+
scale_colour_gradientn(colors = c("#e6e6e6",
"#e60000",
"#e60000",
"#e60000",
"#e60000"),
breaks = c(0,
0.5,
1))+
labs(title = i)+
theme(plot.title = element_text(hjust = 0.5)) +
theme(
axis.line = element_line(color = 'black'),
panel.background = element_rect(fill = 'white', color = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank()
)
plot(p)
dev.off()
}
```
## fig3b_linear
```{r}
markers = colnames(intestline)[18:34]
scale_marker = function(x){(x-min(x))/(max(x)-min(x))}
markers = c("Villin","Olfm4","Ki67","SMA","Lysozyme")
for(i in markers){
pdf(file = paste0(figure_dir,"/V2fig3b_linear_",i,".pdf"),width = 30,height = 4)
# i = "Lysozyme"
tmp_data = plot_data[,c("Length","Thickness",i)]
tmp_data$scaled = scale_marker(tmp_data[,i])
## overlay large values on top
tmp_data = tmp_data[order(tmp_data[, "scaled"],decreasing = FALSE),]
p = ggplot(tmp_data,aes(Length,Thickness,color=scaled))+
geom_point(size=0.01)+
scale_colour_gradientn(colors = c("#e6e6e6",
"#e60000",
"#e60000",
"#e60000",
"#e60000"),
breaks = c(0,
0.5,
1))+
labs(title = i)+
theme(plot.title = element_text(hjust = 0.5)) +
theme(
axis.line = element_line(color = 'black'),
panel.background = element_rect(fill = 'white', color = 'black'),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank()
)
plot(p)
dev.off()
}
```