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Fig_1_Viz.Rmd
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---
title: "Fig_1_Viz"
author: "Troy McDiarmid"
date: "2024-01-13"
output: html_document
---
```{r setup, include=FALSE}
library(tidyverse)
```
```{r}
##Lmax visualizations
U6_Pro_combos <- read_csv("/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/Fig1_Final_Figure_Datasets/240208_U6_Pro_combos.csv")
ggplot(U6_Pro_combos, aes(x = Lmax)) +
geom_histogram(adjust=1.5, fill = "black", binwidth = 1) +
theme_classic() +
theme(axis.line = element_line(colour = 'black', size = 0.8)) +
theme(axis.ticks = element_line(colour = "black", size = 0.8)) +
scale_y_continuous(breaks = c(0,2500,5000)) +
theme(axis.ticks.length=unit(.2, "cm")) +
labs(title = "", x = "", y = "") +
theme(legend.position = "none") +
xlim(0,50) +
theme(text = element_text(family="Arial", colour = "black", size = 44))
ggsave("All_Lmax_Dist.jpeg", width = 16, height = 3.5, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
##Filtering for just evo-evo interactions
DivU6_Prom_Lmax <- U6_Pro_combos %>%
filter(!grepl("Syn", Name_A)) %>%
filter(!grepl("Syn", Name_B))
ggplot(DivU6_Prom_Lmax, aes(x = Lmax)) +
geom_histogram(adjust=1.5, fill = "#56B4E9", binwidth = 1) +
theme_classic() +
theme(axis.line = element_line(colour = 'black', size = 0.8)) +
theme(axis.ticks = element_line(colour = "black", size = 0.8)) +
scale_y_continuous(breaks = c(0,750,1500)) +
theme(axis.ticks.length=unit(.2, "cm")) +
labs(title = "", x = "", y = "") +
theme(legend.position = "none") +
xlim(0,50) +
theme(text = element_text(family="Arial", colour = "black", size = 44))
ggsave("Div_Lmax_Dist.jpeg", width = 16, height = 3.5, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
##Filtering for just synthetic-synthetic interactions
SynU6_Pro_Lmax <- U6_Pro_combos %>%
filter(grepl("Syn", Name_A)) %>%
filter(grepl("Syn", Name_B))
ggplot(SynU6_Pro_Lmax, aes(x = Lmax)) +
geom_histogram(adjust=1.5, fill = "#999999", binwidth = 1) +
theme_classic() +
theme(axis.line = element_line(colour = 'black', size = 0.8)) +
theme(axis.ticks = element_line(colour = "black", size = 0.8)) +
scale_y_continuous(breaks = c(0,600,1200)) +
theme(axis.ticks.length=unit(.2, "cm")) +
labs(title = "", x = "", y = "") +
theme(legend.position = "none") +
xlim(0,50) +
theme(text = element_text(family="Arial", colour = "black", size = 44))
ggsave("Syn_Lmax_Dist.jpeg", width = 16, height = 3.5, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
```
```{r}
##Reading in data
U6_Promoters <- read_csv("/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/Fig1_Final_Figure_Datasets/U6_Edit_Scores_Comparison_Table.csv")
##Removing the four sequences that did not meet Lmax < 40
U6_Promoters <- U6_Promoters %>%
filter(!Name %in% c("Salmo_salar_RNU6-8_ENSSSAG00000015687", "Callorhinchus_milii_RNU6-8_ENSCMIG00000009541", "Rhinolophus_ferrumequinum_ENSRFEG00010003483", "Weissman_sU6-2"))
##Add colour labels
hRNU61_Promoter <- U6_Promoters %>%
filter(Name == "Human_Weissman_RNU6-1")
hRNU61_Promoter$Promoter_Lib <- "hRNU61"
SynU6_Promoters <- U6_Promoters %>%
filter(grepl("Syn", Name))
SynU6_Promoters$Promoter_Lib <- "Synthetic"
DivU6_Promoters <- U6_Promoters %>%
filter(!grepl("Syn", Name)) %>%
filter(!Name == "Human_Weissman_RNU6-1")
DivU6_Promoters$Promoter_Lib <- "Diverse"
U6_Promoters <- rbind(hRNU61_Promoter, SynU6_Promoters, DivU6_Promoters)
##Making promoters FASTA for sequence identity calculation
U6_Pro_ID <- U6_Promoters %>%
select(Name) %>%
dplyr::rename(id = Name) %>%
mutate(number = row_number())
U6_Pro_ID$symbol <-">"
U6_Pro_ID <- U6_Pro_ID %>%
unite("id", symbol, id, sep = "")
U6_Pro_ID_2 <- U6_Promoters %>%
select(U6_Promoter_Seq) %>%
dplyr::rename(id = U6_Promoter_Seq) %>%
mutate(number = row_number())
U6_Pro_ID_3 <- rbind(U6_Pro_ID, U6_Pro_ID_2)
U6_Pro_ID_3 <- U6_Pro_ID_3 %>%
arrange(number) %>%
dplyr::select(id)
write_csv(U6_Pro_ID_3, "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/Fig1_Final_Figure_Datasets/U6_Promoters_Fasta.fa", col_names = FALSE)
##Calculating median edit score across contexts
U6_Promoters <- U6_Promoters %>%
rowwise() %>%
mutate(Median_Edit_Score_Across_Contexts = median(K562:iPSC))
##Reading in percent sequence identity to hRNU6-1p
hRNU6p_PID <- read_csv("/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/Fig1_Final_Figure_Datasets/hRNU61p_Percent_Seq_Identity.csv") %>%
type_convert()
U6_Promoters <- cbind(U6_Promoters, hRNU6p_PID)
##Reordering binding and ordering factors for plotting
##Add colour labels
hRNU61_Promoter <- U6_Promoters %>%
filter(Name == "Human_Weissman_RNU6-1")
hRNU61_Promoter$Promoter_Lib <- "hRNU61"
SynU6_Promoters <- U6_Promoters %>%
filter(grepl("Syn", Name))
SynU6_Promoters$Promoter_Lib <- "Synthetic"
DivU6_Promoters <- U6_Promoters %>%
filter(!grepl("Syn", Name)) %>%
filter(!Name %in% c("Human_Weissman_RNU6-1"))
DivU6_Promoters$Promoter_Lib <- "Diverse"
U6_Promoters <- rbind(SynU6_Promoters, DivU6_Promoters, hRNU61_Promoter)
U6_Promoters$Promoter_Lib <- factor(U6_Promoters$Promoter_Lib, levels = c("Synthetic", "Diverse", "hRNU61"))
##Correlation plot of edit scores
ggplot(U6_Promoters, aes(x = log2(K562), y = log2(HEK293T), colour = Promoter_Lib, size = Promoter_Lib)) +
geom_point() +
scale_color_manual(values=c("#D2D5D5", "#56B4E9", "black")) +
scale_size_manual(values=c(4, 4, 6)) +
scale_x_continuous(labels = scales::number_format(accuracy = 0.1)) +
scale_y_continuous(labels = scales::number_format(accuracy = 0.1)) +
theme_classic() +
theme(axis.line = element_line(colour = 'black', size = 0.8)) +
theme(axis.ticks = element_line(colour = "black", size = 0.8)) +
theme(axis.ticks.length=unit(.2, "cm")) +
labs(title = "", x = "", y = "") +
theme(legend.position = "none") +
theme(text = element_text(family="Arial", colour = "black", size = 39), plot.margin = margin(0, 15, 0, 20))
ggsave("K562_HEK293T_Corr.jpeg", width = 9, height = 7, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
ggplot(U6_Promoters, aes(x = log2(K562), y = log2(iPSC), colour = Promoter_Lib, size = Promoter_Lib)) +
geom_point() +
scale_color_manual(values=c("#D2D5D5", "#56B4E9", "black")) +
scale_size_manual(values=c(4, 4, 6)) +
scale_x_continuous(labels = scales::number_format(accuracy = 0.1)) +
scale_y_continuous(labels = scales::number_format(accuracy = 0.1)) +
theme_classic() +
theme(axis.line = element_line(colour = 'black', size = 0.8)) +
theme(axis.ticks = element_line(colour = "black", size = 0.8)) +
theme(axis.ticks.length=unit(.2, "cm")) +
labs(title = "", x = "", y = "") +
theme(legend.position = "none") +
theme(text = element_text(family="Arial", colour = "black", size = 39), plot.margin = margin(0, 15, 0, 20))
ggsave("K562_iPSC_Corr.jpeg", width = 9, height = 7, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
ggplot(U6_Promoters, aes(x = log2(HEK293T), y = log2(iPSC), colour = Promoter_Lib, size = Promoter_Lib)) +
geom_point() +
scale_color_manual(values=c("#D2D5D5", "#56B4E9", "black")) +
scale_size_manual(values=c(4, 4, 6)) +
scale_x_continuous(labels = scales::number_format(accuracy = 0.1)) +
scale_y_continuous(labels = scales::number_format(accuracy = 0.1)) +
theme_classic() +
theme(axis.line = element_line(colour = 'black', size = 0.8)) +
theme(axis.ticks = element_line(colour = "black", size = 0.8)) +
theme(axis.ticks.length=unit(.2, "cm")) +
labs(title = "", x = "", y = "") +
theme(legend.position = "none") +
theme(text = element_text(family="Arial", colour = "black", size = 39), plot.margin = margin(0, 15, 0, 20))
ggsave("HEK293T_iPSC_Corr.jpeg", width = 9, height = 7, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
##Calculating correlation between different cell contexts
cor.test(U6_Promoters$K562, U6_Promoters$HEK293T)
cor.test(U6_Promoters$K562, U6_Promoters$iPSC)
cor.test(U6_Promoters$iPSC, U6_Promoters$HEK293T)
##Plotting sequence identity by median edit score across contexts
ggplot(U6_Promoters, aes(x = hRNU61p_Percent_Seq_Identity, y = log2(Median_Edit_Score_Across_Contexts), colour = Promoter_Lib, size = Promoter_Lib)) +
geom_point() +
scale_color_manual(values=c("#D2D5D5", "#56B4E9", "black")) +
scale_size_manual(values=c(4, 4, 6)) +
scale_x_continuous(labels = scales::number_format(accuracy = 1.0)) +
scale_y_continuous(labels = scales::number_format(accuracy = 0.1)) +
theme_classic() +
theme(axis.line = element_line(colour = 'black', size = 0.8)) +
theme(axis.ticks = element_line(colour = "black", size = 0.8)) +
theme(axis.ticks.length=unit(.2, "cm")) +
labs(title = "", x = "", y = "") +
theme(legend.position = "none") +
xlim(0,100) +
theme(text = element_text(family="Arial", colour = "black", size = 39), plot.margin = margin(0, 15, 0, 20))
ggsave("hRNU61_PID_v_Median_Edit_Score.jpeg", width = 9, height = 7, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
##Calculating correlation between hRNU61p and sequence identity, with and without hRNU61p included
cor.test(U6_Promoters$hRNU61p_Percent_Seq_Identity, U6_Promoters$Median_Edit_Score_Across_Contexts, method = "spearman")
U6_Promoters_No_hRNU61 <- U6_Promoters %>%
filter(!Name == "Human_Weissman_RNU6-1")
cor.test(U6_Promoters_No_hRNU61$hRNU61p_Percent_Seq_Identity, U6_Promoters_No_hRNU61$Median_Edit_Score_Across_Contexts, method = "spearman")
```
```{r}
##Edit score Heatmap
U6_Promoters_Heatmap <- U6_Promoters %>%
filter(K562 > 0 & HEK293T > 0 & iPSC > 0) %>%
pivot_longer(cols = K562:iPSC, names_to = "Cell_Type", values_to = "Edit_Score")
ggplot(U6_Promoters_Heatmap, aes(x = reorder(Name, Median_Edit_Score_Across_Contexts), y = Cell_Type, fill = log2(Edit_Score))) +
geom_tile()
ggsave("U6_Heatmap_legend.jpeg", width = 38, height = 2.5, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
ggplot(U6_Promoters_Heatmap, aes(x = reorder(Name, Median_Edit_Score_Across_Contexts), y = Cell_Type, fill = log2(Edit_Score))) +
theme_void() +
geom_tile() +
theme(axis.ticks.length=unit(0, "cm")) +
labs(title = "", x = "", y = "")
ggsave("U6_Heatmap.jpeg", width = 38, height = 2.5, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
##Categorical promoter class heatmap
ggplot(U6_Promoters_Heatmap, aes(reorder(Name, Median_Edit_Score_Across_Contexts), y = 1, fill= Promoter_Lib)) +
geom_tile(color = "white",
lwd = 4,
linetype = 1) +
scale_fill_manual(values=c("#D2D5D5", "#56B4E9", "black")) +
theme_void() +
theme(legend.position="none") +
labs(title = "", x = "", y = "")
ggsave("U6_Promoter_Lib_Heatmap.jpeg", width = 38, height = 0.7, path = "/Users/troymcdiarmid/Documents/U6_pro_series/Figs/Pub_Figs/")
```