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4_figure_generation.Rmd
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4_figure_generation.Rmd
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---
title: "Generating scREMOTE Figures"
author: "Andy Tran"
date: "09 May 2021"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{scClassify}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
editor_options:
chunk_output_type: console
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
knitr::opts_chunk$set(fig.width=8, fig.height=6)
```
# Import Necessary Packages
```{r, include = FALSE}
library(tidyverse)
library(Matrix)
library(glmnet)
library(pheatmap)
library(Rtsne)
library(umap)
library(scater)
library(limma)
library(gganimate)
```
Load Workspace Gata3 scREMOTE
```{r}
load("2021-05-27_scREMOTE_figs_Gata3.RData")
```
initial visualisation
```{r, fig.width = 7, fig.height = 5}
pca_coords <- data.frame(reducedDim(E_sce, "PCA"))
pca_coords$cluster <- factor(cell_types$celltype, levels = c("HairShaft", "IRS", "TAC"))
ggplot(pca_coords, aes(x = PC1, y = PC2)) +
geom_point(aes(color = cluster), size = 1.5) +
scale_color_manual(values = c("#6699FF" , "#009933", "#FF9900"))+
theme_classic() +
labs(color = "Cell Type")
```
```{r, fig.width = 7, fig.height = 5}
library(viridis)
pca_coords$size <- colSums(E)
ggplot(pca_coords, aes(x = PC1, y = PC2)) +
geom_point(aes(color = size), size = 1.5) +
scale_color_viridis()+
theme_classic() +
labs(color = "UMI Count")
```
```{r, fig.width = 7, fig.height = 5}
ggplot(pca_coords, aes(x = PC2, y = PC3)) +
geom_point(aes(color = cluster), size = 1.5) +
scale_color_manual(values = c("#6699FF" , "#009933", "#FF9900"))+
theme_classic() +
labs(color = "Cell Type")
```
```{r, fig.width = 7, fig.height = 5}
ggplot(pca_coords, aes(x = PC2, y = PC3)) +
geom_point(aes(color = size), size = 1.5) +
scale_color_viridis()+
theme_classic() +
labs(color = "UMI Count")
```
```{r, fig.width = 5, fig.height = 5}
ggplot(pca_coords, aes(x = PC2, y = PC3)) +
geom_point(aes(color = cluster), size = 1) +
scale_color_manual(values = c("#6699FF" , "#009933", "#FF9900"))+
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 1)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 4)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 8)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r}
top_genes_IRS <- rownames(arrange(-diff.genes,t))[1:4]
top_genes_IRS <-top_genes_IRS[c(1,2,4)]
top_genes_HairShaft <- rownames(arrange(diff.genes,t))[1:3]
top_genes <- c(top_genes_IRS,top_genes_HairShaft)
filtered_all_E <- all_E %>% filter(gene %in% top_genes)
ggplot(filtered_all_E,aes(x = time, y = mean_exp, color = factor(gene, levels = top_genes))) +
geom_line(size = 1) +
geom_point() +
scale_color_manual(name = "Marker Genes",
values = c("#66CC33", "#006600", "#339933","#003399", "#0066CC", "#3399FF"),
labels = top_genes) +
xlab("Time Step") +
ylab("Log Transformed Expression") +
scale_x_continuous(expand = c(0, 0), limits = c(0, rep + 0.5)) +
theme_classic() +
theme(axis.text = element_text(size=11),
axis.title = element_text(size=14),
legend.text = element_text(size=11),
legend.title = element_text(size=13))
```
```{r, fig.width = 8, fig.height = 7}
pheatmap(cor(coefs[,-1]), cluster_rows = F, cluster_cols = F)
```
Load Workspace Runx1 scREMOTE
```{r}
load("2021-05-27_scREMOTE_figs_Runx1.RData")
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 1)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 4)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 8)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r}
top_genes_IRS <- rownames(arrange(-diff.genes,t))[1:4]
top_genes_IRS <-top_genes_IRS[c(1,2,4)]
top_genes_HairShaft <- rownames(arrange(diff.genes,t))[1:3]
top_genes <- c(top_genes_IRS,top_genes_HairShaft)
filtered_all_E <- all_E %>% filter(gene %in% top_genes)
ggplot(filtered_all_E,aes(x = time, y = mean_exp, color = factor(gene, levels = top_genes))) +
geom_line(size = 1) +
geom_point() +
scale_color_manual(name = "Marker Genes",
values = c("#66CC33", "#006600", "#339933","#003399", "#0066CC", "#3399FF"),
labels = top_genes) +
xlab("Time Step") +
ylab("Log Transformed Expression") +
scale_x_continuous(expand = c(0, 0), limits = c(0, rep + 0.5)) +
theme_classic() +
theme(axis.text = element_text(size=11),
axis.title = element_text(size=14),
legend.text = element_text(size=11),
legend.title = element_text(size=13))
```
```{r, fig.width = 8, fig.height = 7}
pheatmap(cor(coefs[,-1]), cluster_rows = F, cluster_cols = F)
```
Load Workspace Gata3 Coexpression
```{r}
load("2021-05-09_coexpression_figs_Gata3.RData")
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 1)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 4)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 8)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
Load Workspace Runx1 Coexpression
```{r}
load("2021-05-09_coexpression_figs_Runx1.RData")
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 1)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 4)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r, fig.width = 5, fig.height = 5}
combined_pca_coords_temp <- filter(combined_pca_coords, time == 8)
ggplot(aes(x = PC2, y = PC3),data = combined_pca_coords_temp) +
scale_color_manual(name = "Cell Types", values = c("#6699FF" , "#009933", "#FF9900","#333333"), labels = c("Hair Shaft", "IRS", "TAC","Reprogrammed"))+
geom_point(aes(color = factor(cluster, levels = c("HairShaft", "IRS", "TAC","intermediary"))), size = 1, shape = 19) +
theme_classic() +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.text = element_blank(),
axis.title = element_text(size=14))
```
```{r}
sessionInfo()
```