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Mouse5TG_FinalFigures.Rmd
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Mouse5TG_FinalFigures.Rmd
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---
title: "Mouse5TG_FinalFigures"
output: html_document
date: "2023-05-01"
---
# Load libraries
```{r}
library(Seurat)
library(dplyr)
library(ggplot2)
library(ggpubr)
library(grid)
library(gridExtra)
library(patchwork)
library(flextable)
library(rstatix)
library(reshape2)
```
# Load in stromal data
```{r}
stromals <- readRDS("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/objects/Rerun_Mouse5TG_StromalsOnly_AnnotatedObject6_21PCs_NoLib_FIXEDLIBRARIES_6.rds")
healthy <- subset(stromals, subset = case.control == "Healthy")
myeloma <- subset(stromals, subset = case.control == "Myeloma")
bmecs <- readRDS("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/objects/5TGM1_BMEC_Object.rds")
msclin <- readRDS("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/objects/5TGM1_MSCOLC_Object.rds")
```
# Figure 3A
```{r}
# A - UMAP
library(scales)
show_col(hue_pal()(7))
subtype <- stromals
# Without cell count legend
Idents(stromals) <- "celltypes_ECsubbed"
figure.3a <- DimPlot(stromals, label = T, cols = c("#F8766D", "#C49A00", "#53B400", "#00C094", "#00B6EB", "#A58AFF", "#FB61D7")) + NoLegend()
#ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/StromalCells_UMAP.png", height = 6, width = 6)
# With cell count legend
DimPlot(stromals) + scale_color_manual(labels = c("Sinusoidal ECs (n = 1,881)", "Fibroblasts (n = 3,363)", "MSCs (n = 3,030)", "OLCs (n = 1,248)", "Pericytes (n = 1,615)",
"Arterial ECs (n = 2,961)", "Chondrocytes (n = 121)"),
values = c("#F8766D", "#C49A00", "#53B400", "#00C094", "#00B6EB", "#A58AFF", "#FB61D7"))
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/StromalCells_UMAP_WithCellCounts.png", height = 6, width = 8)
```
Figure 3B - Feature Plots of Main Marker Genes
```{r}
newNames <- as.character(stromals@meta.data$celltypes_ECsubbed)
newNames <- replace(newNames, newNames=="Sinusoidal ECs", "SEC")
newNames <- replace(newNames, newNames=="Arterial ECs", "AEC")
newNames <- replace(newNames, newNames=="MSCs", "MSC")
newNames <- replace(newNames, newNames=="OLCs", "OLC")
stromals@meta.data$celltypes_ECsubbed_nameFixed <- newNames
stromals@meta.data$celltypes_ECsubbed_nameFixed <- factor(stromals@meta.data$celltypes_ECsubbed_nameFixed, levels = c("MSC", "OLC", "SEC", "AEC", "Fibroblasts", "Chondrocytes", "Pericytes"))
Idents(stromals) <- "celltypes_ECsubbed_nameFixed"
p1.ft <- FeaturePlot(stromals, features = c("Lepr")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p2.ft <- FeaturePlot(stromals, features = c("Bglap")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p3.ft <- FeaturePlot(stromals, features = c("Fn1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p4.ft <- FeaturePlot(stromals, features = c("Sox9")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p5.ft <- FeaturePlot(stromals, features = c("Acta2")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p6.ft <- FeaturePlot(stromals, features = c("Cdh5")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
figure.3b <- (p1.ft | p2.ft | p3.ft | p4.ft | p5.ft | p6.ft)
p1.ft <- VlnPlot(stromals, features = c("Lepr")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p2.ft <- VlnPlot(stromals, features = c("Bglap")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p3.ft <- VlnPlot(stromals, features = c("Fn1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p4.ft <- VlnPlot(stromals, features = c("Sox9")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p5.ft <- VlnPlot(stromals, features = c("Acta2")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p6.ft <- VlnPlot(stromals, features = c("Cdh5")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
figure.3c <- (p1.ft | p2.ft | p3.ft | p4.ft | p5.ft | p6.ft)
figure.3b
ggsave("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/Figure3_FeaturePlots.png", height = 2.5, width = 12)
figure.3c
ggsave("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/Figure3_ViolinPlots.png", height = 3, width = 12)
```
Figure 3C - Relative Abundance of Stromal Pops
```{r fig.height = 4, fig.width = 10}
# B - Relative abundances
healthy.da <- data.frame(table(healthy@meta.data$celltypes_ECsubbed)/sum(table(healthy@meta.data$celltypes_ECsubbed)))
healthy.da$condition <- "Healthy"
myeloma.da <- data.frame(table(myeloma@meta.data$celltypes_ECsubbed)/sum(table(myeloma@meta.data$celltypes_ECsubbed)))
myeloma.da$condition <- "Myeloma"
combined.da <- rbind(myeloma.da, healthy.da)
melted.da.df <- melt(combined.da, id.vars = c("Var1", "condition"))
colnames(melted.da.df) <- c("Celltype", "Condition", "Balls", "RA")
melted.da.df$Condition <- factor(melted.da.df$Condition, levels = c("Myeloma", "Healthy"))
melted.da.df$Celltype <- factor(melted.da.df$Celltype)
levels(melted.da.df$Celltype)
melted.da.df$Celltype <- factor(melted.da.df$Celltype, levels = c("MSCs", "OLCs", "Sinusoidal ECs", "Arterial ECs", "Fibroblasts", "Chondrocytes", "Pericytes"))
# Grouped bar
figure.3c <- ggplot(melted.da.df, aes(fill = Condition, y = RA, x = Celltype)) + geom_bar(position = "dodge", stat = "identity") +
ylab("Relative Abundance") + xlab("") +
theme_minimal() +
theme(legend.position = "bottom",
legend.text = element_text(size = 16)) +
theme(axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 16)) +
scale_x_discrete(labels = c("MSC", "OLC", "SEC", "AEC", "Fibroblasts", "Chondrocytes", "Pericytes"))
```
Figure 3D - pseudosampled relative abundances
# Create storage df
```{r}
# Total cell counts by condition
myeloma.abundances <- myeloma@meta.data$celltypes_ECsubbed
healthy.abundances <- healthy@meta.data$celltypes_ECsubbed
# Relative abundances by condition
#null.relabuns <- table(stromals@meta.data$celltypes_ECsubbed)/sum(table(stromals@meta.data$celltypes_ECsubbed))
myeloma.relabuns <- table(myeloma@meta.data$celltypes_ECsubbed)/sum(table(myeloma@meta.data$celltypes_ECsubbed))
healthy.relabuns <- table(healthy@meta.data$celltypes_ECsubbed)/sum(table(healthy@meta.data$celltypes_ECsubbed))
# Isolate values for each observed cell type relative abundance for MM
mm.observed.sec <- myeloma.relabuns[1]
mm.observed.fibro <- myeloma.relabuns[2]
mm.observed.msc <- myeloma.relabuns[3]
mm.observed.olc <- myeloma.relabuns[4]
mm.observed.peri <- myeloma.relabuns[5]
mm.observed.aec <- myeloma.relabuns[6]
mm.observed.chondro <- myeloma.relabuns[7]
# Isolate values for each observed cell type relative abundance for Healthy
healthy.observed.sec <- healthy.relabuns[1]
healthy.observed.fibro <- healthy.relabuns[2]
healthy.observed.msc <- healthy.relabuns[3]
healthy.observed.olc <- healthy.relabuns[4]
healthy.observed.peri <- healthy.relabuns[5]
healthy.observed.aec <- healthy.relabuns[6]
healthy.observed.chondro <- healthy.relabuns[7]
# Total cells by condition
n_cells_myeloma <- ncol(myeloma)
n_cells_healthy <- ncol(healthy)
# Randomly subsample with replacement and spit out relative abundances
myeloma.resamples <- lapply(1:1000, function(i) table(sample(myeloma.abundances, replace = T, prob = ))/n_cells_myeloma)
healthy.resamples <- lapply(1:1000, function(i) table(sample(healthy.abundances, replace = T, prob = ))/n_cells_healthy)
# Relative abundance distributions for each celltype -- MM
mm.resamples.sec <- sapply(myeloma.resamples,"[[",1)
mm.resamples.fibro <- sapply(myeloma.resamples,"[[",2)
mm.resamples.msc <- sapply(myeloma.resamples,"[[",3)
mm.resamples.olc <- sapply(myeloma.resamples,"[[",4)
mm.resamples.peri <- sapply(myeloma.resamples,"[[",5)
mm.resamples.aec <- sapply(myeloma.resamples,"[[",6)
mm.resamples.chondro <- sapply(myeloma.resamples,"[[",7)
# Relative abundance distributions for each celltype -- Healthy
healthy.resamples.sec <- sapply(healthy.resamples,"[[",1)
healthy.resamples.fibro <- sapply(healthy.resamples,"[[",2)
healthy.resamples.msc <- sapply(healthy.resamples,"[[",3)
healthy.resamples.olc <- sapply(healthy.resamples,"[[",4)
healthy.resamples.peri <- sapply(healthy.resamples,"[[",5)
healthy.resamples.aec <- sapply(healthy.resamples,"[[",6)
healthy.resamples.chondro <- sapply(healthy.resamples,"[[",7)
sec.plotting.df <- melt(data.frame(Myeloma = mm.resamples.sec, Healthy = healthy.resamples.sec, Celltype = "SEC"))
colnames(sec.plotting.df)[2] <- "Condition"
fibro.plotting.df <- melt(data.frame(Myeloma = mm.resamples.fibro, Healthy = healthy.resamples.fibro, Celltype = "Fibroblasts"))
colnames(fibro.plotting.df)[2] <- "Condition"
msc.plotting.df <- melt(data.frame(Myeloma = mm.resamples.msc, Healthy = healthy.resamples.msc, Celltype = "MSC"))
colnames(msc.plotting.df)[2] <- "Condition"
olc.plotting.df <- melt(data.frame(Myeloma = mm.resamples.olc, Healthy = healthy.resamples.olc, Celltype = "OLC"))
colnames(olc.plotting.df)[2] <- "Condition"
peri.plotting.df <- melt(data.frame(Myeloma = mm.resamples.peri, Healthy = healthy.resamples.peri, Celltype = "Pericytes"))
colnames(peri.plotting.df)[2] <- "Condition"
aec.plotting.df <- melt(data.frame(Myeloma = mm.resamples.aec, Healthy = healthy.resamples.aec, Celltype = "AEC"))
colnames(aec.plotting.df)[2] <- "Condition"
chondro.plotting.df <- melt(data.frame(Myeloma = mm.resamples.chondro, Healthy = healthy.resamples.chondro, Celltype = "Chondrocytes"))
colnames(chondro.plotting.df)[2] <- "Condition"
full.plotting.df <- do.call("rbind", list(sec.plotting.df, fibro.plotting.df, msc.plotting.df, olc.plotting.df, peri.plotting.df, aec.plotting.df, chondro.plotting.df))
sec.stat.test <- sec.plotting.df %>%
t_test(value ~ Condition) %>%
add_significance()
fibro.stat.test <- fibro.plotting.df %>%
t_test(value ~ Condition) %>%
add_significance()
msc.stat.test <- msc.plotting.df %>%
t_test(value ~ Condition) %>%
add_significance()
olc.stat.test <- olc.plotting.df %>%
t_test(value ~ Condition) %>%
add_significance()
peri.stat.test <- peri.plotting.df %>%
t_test(value ~ Condition) %>%
add_significance()
aec.stat.test <- aec.plotting.df %>%
t_test(value ~ Condition) %>%
add_significance()
chondro.stat.test <- chondro.plotting.df %>%
t_test(value ~ Condition) %>%
add_significance()
```
Figure 3D continued -- bootstrapped relative abundances
```{r fig.height = 3, fig.width = 10}
sec.bxp <- ggboxplot(sec.plotting.df, x = "Condition", y = "value", fill = "Condition", notch = TRUE) +
ylab("") + xlab("") + ggtitle("SEC") +
theme_bw(base_size = 16) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(hjust = 0.5)) + NoLegend()
sec.stat.test <- sec.stat.test %>% add_xy_position("Condition")
sec.bxp <- sec.bxp +
stat_pvalue_manual(sec.stat.test, label = "T-test, p = {p}") +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))
#############################################################
fibro.bxp <- ggboxplot(fibro.plotting.df, x = "Condition", y = "value", fill = "Condition", notch = TRUE) +
ylab("") + xlab("") + ggtitle("Fibroblasts") +
theme_bw(base_size = 16) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(hjust = 0.5)) + NoLegend()
fibro.stat.test <- fibro.stat.test %>% add_xy_position("Condition")
fibro.bxp <- fibro.bxp +
stat_pvalue_manual(fibro.stat.test, label = "T-test, p = {p}") +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))
#############################################################
msc.bxp <- ggboxplot(msc.plotting.df, x = "Condition", y = "value", fill = "Condition", notch = TRUE) +
ylab("Relative Abundance") + xlab("") + ggtitle("MSC") +
theme_bw(base_size = 16) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(hjust = 0.5)) + NoLegend()
msc.stat.test <- msc.stat.test %>% add_xy_position("Condition")
msc.bxp <- msc.bxp +
stat_pvalue_manual(msc.stat.test, label = "T-test, p = {p}") +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))
#############################################################
olc.bxp <- ggboxplot(olc.plotting.df, x = "Condition", y = "value", fill = "Condition", notch = TRUE) +
ylab("") + xlab("") + ggtitle("OLC") +
theme_bw(base_size = 16) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(hjust = 0.5)) + NoLegend()
olc.stat.test <- olc.stat.test %>% add_xy_position("Condition")
olc.bxp <- olc.bxp +
stat_pvalue_manual(olc.stat.test, label = "T-test, p = {p}") +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))
#############################################################
peri.bxp <- ggboxplot(peri.plotting.df, x = "Condition", y = "value", fill = "Condition", notch = TRUE) +
ylab("") + xlab("") + ggtitle("Pericytes") +
theme_bw(base_size = 16) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(hjust = 0.5)) + NoLegend() # Keeping legend for this one
peri.stat.test <- peri.stat.test %>% add_xy_position("Condition")
peri.bxp <- peri.bxp +
stat_pvalue_manual(peri.stat.test, label = "T-test, p = {p}") +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))
#############################################################
aec.bxp <- ggboxplot(aec.plotting.df, x = "Condition", y = "value", fill = "Condition", notch = TRUE) +
ylab("") + xlab("") + ggtitle("AEC") +
theme_bw(base_size = 16) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(hjust = 0.5)) + NoLegend()
aec.stat.test <- aec.stat.test %>% add_xy_position("Condition")
aec.bxp <- aec.bxp +
stat_pvalue_manual(aec.stat.test, label = "T-test, p = {p}") +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))
#############################################################
chondro.bxp <- ggboxplot(chondro.plotting.df, x = "Condition", y = "value", fill = "Condition", notch = TRUE) +
ylab("") + xlab("") + ggtitle("Chondrocytes") +
theme_bw(base_size = 16) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(hjust = 0.5)) + NoLegend()
chondro.stat.test <- chondro.stat.test %>% add_xy_position("Condition")
chondro.bxp <- chondro.bxp +
stat_pvalue_manual(chondro.stat.test, label = "T-test, p = {p}") +
scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))
figure.3d <- msc.bxp | olc.bxp | sec.bxp | aec.bxp | fibro.bxp | chondro.bxp | peri.bxp #+ plot_layout(ncol = 7, guides = "collect")
#ggsave("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/1000x_Bootstrap_CelltypeBoxplots.png", height = 5, width = 20)
# Patchwork trying
#figure.3c <- msc.box + olc.box + fibro.box + chondro.box + aEC.box + sEC.box + peri.box + plot_layout(ncol = 7, guides = "collect")
#gt <- patchwork::patchworkGrob(pseudo.boxplots)
#gt.fixed <- gridExtra::grid.arrange(gt, left = "Relative Abundance", bottom = "Cell Type")
#ggsave(plot = gt.fixed, filename = "/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/figures/CellTypeRelativeAbundance_Boxplot_Condition_Pseudosampled_05PercDownSample.png", width = 12, height = 3)
```
# Supplementary Figures X and Y - Violin Plots of Main Marker Genes?
```{r}
# D - Violin Plots
library(cowplot)
p1 <- VlnPlot(stromals, features = c("Lepr")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p2 <- VlnPlot(stromals, features = c("Bglap")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p3 <- VlnPlot(stromals, features = c("Fn1")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p4 <- VlnPlot(stromals, features = c("Sox9")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p5 <- VlnPlot(stromals, features = c("Acta2")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
p6 <- VlnPlot(stromals, features = c("Cdh5")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
#cowplot::plot_grid(p1, p2, p3, p4, p5, p6,
# nrow = 6,
# labels = "auto")
#figure.3d <- p1 | p2 | p3 | p4 | p5 | p6
#figure.3d <- p1 / p2 / p3 / p4 / p5 / p6
#ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/StromalMarkerGene_VlnPlots_Tall.png", height = 18, width = 4)
```
# Figure 3 Patchwork
```{r}
(figure.3a + figure.3b + plot_layout(design = "
AABBBB
AABBBB"))
ggsave("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/Figure3_Top.png", height = 6.5, width = 19)
(figure.3c + figure.3d + plot_layout(design = "
AAAAAA
AAAAAA
BBBBBB
BBBBBB"))
ggsave("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/Figure3_Bottom.png", height = 9, width = 22)
```
# Figure 3 GSEA Table
```{r}
fig3.genesets <- c("Interferon Gamma Response", "Interferon Alpha Response", "Oxidative Phosphorylation", "MYC Targets")
fig3.nes <- c("1.51", "1.47", "1.43", "1.41")
fig3.fdrqval <- c("0.000", "0.005", "0.013", "0.023")
fig3.df <- data.frame(fig3.genesets, fig3.nes, fig3.fdrqval)
colnames(fig3.df) <- c("Gene Set", "NES", "FDR q-val")
flextable(fig3.df) |>
autofit()
```
# Figure 4 - MSC/OLCs
```{r}
# A = Complex heatmap
# B = Condition Split UMAP
# C = Condition Split Pseudotime
# D = Feature plots of Differentiation genes = Lepr, Lpl, Adipoq, Wif1, Spp1 (Opn), Bglap
# E = Violin plots of differentiation genes
```
Figure 4A - BioRender thing
# Figure 4B - MSC/OLC Condition Split UMAP
```{r}
figure.4b <- DimPlot(msclins, split.by = "case.control", cols = c("#F8766D", "#B79F00", "#00BA38", "#00BFC4", "#619CFF", "#F564E3"))
```
# Figure 4C - MSC/OLC Condition Split Pseudotime UMAP
```{r}
# Copy and pasted from TrajectoryAnalysis markdown. Assumes all preprocessing + analysis is complete
get_earliest_principal_node <- function(cds, time_bin="1"){
cell_ids <- which(colData(cds)[, "seurat_clusters"] == time_bin)
closest_vertex <-
cds@principal_graph_aux[["UMAP"]]$pr_graph_cell_proj_closest_vertex
closest_vertex <- as.matrix(closest_vertex[colnames(cds), ])
root_pr_nodes <-
igraph::V(principal_graph(cds)[["UMAP"]])$name[as.numeric(names
(which.max(table(closest_vertex[cell_ids,]))))]
root_pr_nodes
}
msc.cds <- order_cells(msc.cds, root_pr_nodes=get_earliest_principal_node(msc.cds))
figure.4c <- plot_cells(msc.cds, color_cells_by = "pseudotime", label_groups_by_cluster = F, label_cell_groups = F,
label_branch_points = F, label_roots = F, label_leaves = F) + facet_grid(. ~ case.control)
#ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/MSCOLCs_ONLY_Monocle_Pseudotime_ConditionSplit_ProgrammaticRootChoose.png", height = 5, width = 8)
```
# Figure 4D - MSC/OLC Feature plots
```{r}
lepr.ft <- FeaturePlot(subtype, features = c("Lepr")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
lpl.ft <- FeaturePlot(subtype, features = c("Lpl")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
adipoq.ft <- FeaturePlot(subtype, features = c("Adipoq")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
wif1.ft <- FeaturePlot(subtype, features = c("Wif1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
opn.ft <- FeaturePlot(subtype, features = c("Spp1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + labs(title = "Spp1 (Opn)") + NoLegend()
bglap.ft <- FeaturePlot(subtype, features = c("Bglap")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
### Currently adapted for ABL presentation structure !!! ###
figure.4d <- (lepr.ft | lpl.ft | adipoq.ft | wif1.ft | opn.ft | bglap.ft)
figure.4d
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/figures/MSCOLC_ClusterAssignment_FeaturePlotsHorizontal.png", width = 15, height = 3)
```
# Figure 4E - Violin plots
```{r}
lepr.vln <- VlnPlot(subtype, features = c("Lepr")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
lpl.vln <- VlnPlot(subtype, features = c("Lpl")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
adipoq.vln <- VlnPlot(subtype, features = c("Adipoq")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
wif1.vln <- VlnPlot(subtype, features = c("Wif1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
opn.vln <- VlnPlot(subtype, features = c("Spp1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + labs(title = "Spp1 (Opn)") + NoLegend()
bglap.vln <- VlnPlot(subtype, features = c("Bglap")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
figure.4e <- (lepr.vln | lpl.vln | adipoq.vln | wif1.vln | opn.vln | bglap.vln)
figure.4e
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/figures/MSCOLC_ClusterAssignment_VlnPlotsHorizontal.png", width = 15, height = 3)
```
# Figure 4 Patchwork
```{r fig.height = 10, fig.width = 12.5}
layout <- "
AAAACD
AAAACD
AAAACD
BBBBCD
BBBBCD
BBBBCD
####CD
####CD
####CD
"
panel <- figure.4b + figure.4c + figure.4d + figure.4e +
plot_layout(design = layout)
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/Figure4_noHeatmapEEE.png", height = 11, width = 11)
```
# Figure 5 - BMECs
```{r}
# A = Complex heatmap
# B = Condition Split UMAP
# C = Condition Split Pseudotime
# D = Feature plots of Differentiation genes = Lepr, Lpl, Adipoq, Wif1, Spp1 (Opn), Bglap
# E = Violin plots of differentiation genes
```
# Figure 5B - BMEC UMAP
```{r}
figure.5b <- DimPlot(subtype, split.by = "case.control", cols = c("#F8766D", "#B79F00", "#00BA38", "#00BFC4", "#619CFF", "#F564E3"))
```
# Figure 5C - BMEC Pseudotime UMAP
```{r}
# Ran prelim code in the TrajectoryAnalysis markdown
msc.cds <- order_cells(msc.cds, root_pr_nodes=get_earliest_principal_node(msc.cds))
figure.5c <- plot_cells(msc.cds, color_cells_by = "pseudotime", label_groups_by_cluster = F, label_cell_groups = F,
label_branch_points = F, label_roots = F, label_leaves = F) + facet_grid(. ~ case.control)
```
# Figure 5D - Feature plots
```{r}
sca1.ft <- FeaturePlot(subtype, features = c("Ly6a")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + labs(title = "Ly6a (Sca1)") + NoLegend()
cxcl12.ft <- FeaturePlot(subtype, features = c("Cxcl12")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
vegfr4.ft <- FeaturePlot(subtype, features = c("Flt4")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + labs(title = "Flt4 (Vegfr-4)") + NoLegend()
il6st.ft <- FeaturePlot(subtype, features = c("Il6st")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
figure.5d <- sca1.ft | cxcl12.ft | vegfr4.ft | il6st.ft
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/figures/BMEC_FeaturePlots_ABL.png", height = 3, width = 12)
DimPlot(subtype)
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/figures/BMEC_UMAP_ABL.png", height = 5, width = 5)
```
# Figure 5E - Violin plots
```{r}
sca1.vln <- VlnPlot(subtype, features = c("Ly6a")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + labs(title = "Ly6a (Sca1)") + NoLegend()
cxcl12.vln <- VlnPlot(subtype, features = c("Cxcl12")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
vegfr4.vln <- VlnPlot(subtype, features = c("Flt4")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + labs(title = "Flt4 (Vegfr-4)") + NoLegend()
il6st.vln <- VlnPlot(subtype, features = c("Il6st")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
plot.title = element_text(size=12)) + NoLegend()
figure.5e <- sca1.vln | cxcl12.vln | vegfr4.vln | il6st.vln
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/figures/BMEC_ViolinPlots_ABL.png", height = 3, width = 12)
```
# Figure 5 Patchwork
```{r fig.height = 5.6, fig.width = 10}
layout <- "
AAAACD
AAAACD
AAAACD
BBBBCD
BBBBCD
BBBBCD
"
# layout <- "
# AAAAAABBBBBB
# AAAAAABBBBBB
# AAAAAABBBBBB
# ######CCCCCC
# ######DDDDDD
# "
figure.5b + figure.5c + figure.5d + figure.5e +
plot_layout(design = layout)
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/Figure5_noHeatmap.png", height = 7.5, width = 10)
```
#
```{r fig.height = 8, fig.width = 12.5}
Heatmap(matrix.roworder.subset, cluster_rows = F, cluster_columns = TRUE,
row_order = output_gene_order_sub,
show_column_dend = F,
col = col_fun,
column_names_gp = gpar(fontsize = 0), row_names_gp = gpar(fontsize = 4.5),
clustering_distance_columns = "euclidean", clustering_method_columns = "average",
column_dend_height = unit(40,"mm"), row_dend_width = unit(40, "mm"),
top_annotation = annotation,
heatmap_legend_param = list(title = "Scaled Expression")
)
```
```{r}
# D - Violin Plots
library(cowplot)
p1 <- VlnPlot(stromals, features = c("Lepr")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank()) + NoLegend()
p2 <- VlnPlot(stromals, features = c("Bglap")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank()) + NoLegend()
p3 <- VlnPlot(stromals, features = c("Fn1")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank()) + NoLegend()
p4 <- VlnPlot(stromals, features = c("Sox9")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank()) + NoLegend()
p5 <- VlnPlot(stromals, features = c("Acta2")) + theme(axis.text.x = element_blank(), axis.title.x = element_blank()) + NoLegend()
p6 <- VlnPlot(stromals, features = c("Cdh5")) + theme(axis.title.x = element_blank())+ NoLegend()
cowplot::plot_grid(p1, p2, p3, p4, p5, p6,
nrow = 6,
labels = "auto")
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/StromalMarkerGene_VlnPlots_Tall.png", height = 18, width = 4)
# E - Feature Plots
p1.ft <- FeaturePlot(stromals, features = c("Lepr")) + theme(axis.title.x = element_blank()) + NoLegend()
p2.ft <- FeaturePlot(stromals, features = c("Bglap")) + theme(axis.title.x = element_blank()) + NoLegend()
p3.ft <- FeaturePlot(stromals, features = c("Fn1")) + theme(axis.title.x = element_blank()) + NoLegend()
p4.ft <- FeaturePlot(stromals, features = c("Sox9")) + theme(axis.title.x = element_blank()) + NoLegend()
p5.ft <- FeaturePlot(stromals, features = c("Acta2")) + theme(axis.title.x = element_blank()) + NoLegend()
p6.ft <- FeaturePlot(stromals, features = c("Cdh5")) + NoLegend()
cowplot::plot_grid(p1.ft, p2.ft, p3.ft, p4.ft, p5.ft, p6.ft,
nrow = 6,
labels = "auto")
ggsave("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/StromalMarkerGene_FeaturePlots_Tall.png", height = 18, width = 4)
VlnPlot(stromals, features = c("Lepr", "Bglap", "Fn1", "Sox9", "Acta2", "Cdh5"), ncol = 1)
```
# Marker Genes of Main Stromal Populations - Supplementary Figure 4 Violin Plots
```{r}
Idents(stromals) <- "celltypes_ECsubbed"
# MSCs
msc.markers1 <- VlnPlot(stromals, features = c("Lepr")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("MSCs")+ NoLegend()
msc.markers2 <- VlnPlot(stromals, features = c("Adipoq")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
msc.markers3 <- VlnPlot(stromals, features = c("Cxcl12")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# OLCs
olc.markers1 <- VlnPlot(stromals, features = c("Bglap")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("OLCs") + NoLegend()
olc.markers2 <- VlnPlot(stromals, features = c("Spp1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Spp1 (Opn)") + NoLegend()
olc.markers3 <- VlnPlot(stromals, features = c("Sp7")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Fibroblasts
fibro.markers1 <- VlnPlot(stromals, features = c("S100a4")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Fibroblasts") + NoLegend()
fibro.markers2 <- VlnPlot(stromals, features = c("Fn1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
fibro.markers3 <- VlnPlot(stromals, features = c("Dcn")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Chondrocytes
chondro.markers1 <- VlnPlot(stromals, features = c("Col2a1")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Chondrocytes") + NoLegend()
chondro.markers2 <- VlnPlot(stromals, features = c("Sox9")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
chondro.markers3 <- VlnPlot(stromals, features = c("Acan")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Pericytes
peri.markers1 <- VlnPlot(stromals, features = c("Acta2")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Pericytes") + NoLegend()
peri.markers2 <- VlnPlot(stromals, features = c("Myh11")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
peri.markers3 <- VlnPlot(stromals, features = c("Mcam")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# ECs
ec.markers1 <- VlnPlot(stromals, features = c("Cdh5")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("ECs") + NoLegend()
ec.markers2 <- VlnPlot(stromals, features = c("Cd34")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
ec.markers3 <- VlnPlot(stromals, features = c("Pecam1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# AEC/SECs
asec.markers1 <- VlnPlot(stromals, features = c("Flt4")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("AEC/SECs") + labs(title = "Flt4 (Vegfr3)") + NoLegend()
asec.markers2 <- VlnPlot(stromals, features = c("Ly6a")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + labs(title = "Ly6a (Sca1)")+ NoLegend()
asec.markers3 <- VlnPlot(stromals, features = c("Il6st")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
(msc.markers1 | msc.markers2 | msc.markers3) /
(olc.markers1 | olc.markers2 | olc.markers3) /
(fibro.markers1 | fibro.markers2 | fibro.markers3) /
(chondro.markers1 | chondro.markers2 | chondro.markers3) /
(peri.markers1 | peri.markers2 | peri.markers3) /
(ec.markers1 | ec.markers2 | ec.markers3) /
(asec.markers1 | asec.markers2 | asec.markers3) + theme(plot.tag = element_text(size = 8))
ggsave("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/MainStromalPopulations_MarkerGene_ViolinPlots_SupplementaryFigure4.pdf", width = 12, height = 21)
#gt <- patchwork::patchworkGrob(supp3.patchwork)
#pdf("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/MainStromalPopulations_MarkerGene_VlnPlots_SupplementaryFigure3.pdf", width = 15, height = 18)
#gridExtra::grid.arrange(gt, left = textGrob("Scaled Expression", gp=gpar(fontsize=24), rot = 90), bottom = textGrob("Subcluster", gp=gpar(fontsize=24)))
#dev.off()
```
# Supplementary Figure 5 - Main Stromal Marker Gene Feature Plots
```{r}
# MSCs
msc.markers1 <- FeaturePlot(stromals, features = c("Lepr")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("MSCs")+ NoLegend()
msc.markers2 <- FeaturePlot(stromals, features = c("Adipoq")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
msc.markers3 <- FeaturePlot(stromals, features = c("Cxcl12")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# OLCs
olc.markers1 <- FeaturePlot(stromals, features = c("Bglap")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("OLCs") + NoLegend()
olc.markers2 <- FeaturePlot(stromals, features = c("Spp1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Spp1 (Opn)") + NoLegend()
olc.markers3 <- FeaturePlot(stromals, features = c("Sp7")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Fibroblasts
fibro.markers1 <- FeaturePlot(stromals, features = c("S100a4")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Fibroblasts") + NoLegend()
fibro.markers2 <- FeaturePlot(stromals, features = c("Fn1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
fibro.markers3 <- FeaturePlot(stromals, features = c("Dcn")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Chondrocytes
chondro.markers1 <- FeaturePlot(stromals, features = c("Col2a1")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Chondrocytes") + NoLegend()
chondro.markers2 <- FeaturePlot(stromals, features = c("Sox9")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
chondro.markers3 <- FeaturePlot(stromals, features = c("Acan")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Pericytes
peri.markers1 <- FeaturePlot(stromals, features = c("Acta2")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Pericytes") + NoLegend()
peri.markers2 <- FeaturePlot(stromals, features = c("Myh11")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
peri.markers3 <- FeaturePlot(stromals, features = c("Mcam")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# ECs
ec.markers1 <- FeaturePlot(stromals, features = c("Cdh5")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("ECs") + NoLegend()
ec.markers2 <- FeaturePlot(stromals, features = c("Cd34")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
ec.markers3 <- FeaturePlot(stromals, features = c("Pecam1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# AEC/SECs
asec.markers1 <- FeaturePlot(stromals, features = c("Flt4")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("AEC/SECs") + labs(title = "Flt4 (Vegfr3)") + NoLegend()
asec.markers2 <- FeaturePlot(stromals, features = c("Ly6a")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + labs(title = "Ly6a (Sca1)")+ NoLegend()
asec.markers3 <- FeaturePlot(stromals, features = c("Il6st")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
(msc.markers1 | msc.markers2 | msc.markers3) /
(olc.markers1 | olc.markers2 | olc.markers3) /
(fibro.markers1 | fibro.markers2 | fibro.markers3) /
(chondro.markers1 | chondro.markers2 | chondro.markers3) /
(peri.markers1 | peri.markers2 | peri.markers3) /
(ec.markers1 | ec.markers2 | ec.markers3) /
(asec.markers1 | asec.markers2 | asec.markers3) + theme(plot.tag = element_text(size = 8))
ggsave("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/MainStromalPopulations_MarkerGene_FeaturePlots_SupplementaryFigure4.pdf", width = 12, height = 21)
#gt <- patchwork::patchworkGrob(supp4.patchwork)
#pdf("/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/MainStromalPopulations_MarkerGene_FeaturePlots_SupplementaryFigure4.pdf", width = 12, height = 21)
#gridExtra::grid.arrange(gt, left = textGrob("UMAP 1", gp=gpar(fontsize=24), rot = 90), bottom = textGrob("UMAP 2", gp=gpar(fontsize=24)))
#dev.off()
```
# Supplementary Figure XX - Senesecence
```{r}
VlnPlot(msclin, features = c("Cxcl12", "Cxcl1", "Cxcl13", "Ifngr1",
"Il6", "Il6st", "Il7", "Il15",
"Fgf7", "Vegfa", "Kitl", "Icam1",
"Tnfrsf1a", "Igfbp3", "Igfbp4", "Igfbp7",
"Serpine1", "Serpine2", "Lama1", "Lamb1",
"Timp1", "Timp2", "Mmp13", "Mmp14",
"Mif"
), ncol = 5)
ggsave(filename = "/Users/gagled01/morganLab/single-cell/5TGM1_Stromal/figures/Senescence_ViolinPlots.png", width = 13, height = 18)
```
# Supplementary Figure 5 - MSC/OLC subcluster highlight genes
```{r}
# Cluster 0
cluster0.1 <- VlnPlot(subtype, features = c("Lepr")) + theme(axis.title.x = element_blank(), axis.text.y = element_text(size = 15)) + ylab("Cluster 0") + NoLegend()
cluster0.2 <- VlnPlot(subtype, features = c("Lpl")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster0.3 <- VlnPlot(subtype, features = c("Mgp")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster0.4 <- VlnPlot(subtype, features = c("Bmp6")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Cluster 1
cluster1.1 <- VlnPlot(subtype, features = c("Wif1")) + theme(axis.title.x = element_blank(), axis.text.y = element_text(size = 15)) + ylab("Cluster 1") + NoLegend()
cluster1.2 <- VlnPlot(subtype, features = c("Limch1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster1.3 <- VlnPlot(subtype, features = c("Sfrp1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster1.4 <- VlnPlot(subtype, features = c("Tnc")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Cluster 2
cluster2.1 <- VlnPlot(subtype, features = c("Spp1")) + theme(axis.title.x = element_blank(), axis.text.y = element_text(size = 15)) + ylab("Cluster 2") + NoLegend()
cluster2.2 <- VlnPlot(subtype, features = c("Mmp13")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster2.3 <- VlnPlot(subtype, features = c("Postn")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster2.4 <- VlnPlot(subtype, features = c("Col6a3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Cluster 3
cluster3.1 <- VlnPlot(subtype, features = c("Bglap")) + theme(axis.title.x = element_blank(), axis.text.y = element_text(size = 15)) + ylab("Cluster 3") + NoLegend()
cluster3.2 <- VlnPlot(subtype, features = c("Bglap2")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster3.3 <- VlnPlot(subtype, features = c("Col11a1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster3.4 <- VlnPlot(subtype, features = c("Car3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Cluster 4
cluster4.1 <- VlnPlot(subtype, features = c("Btg2")) + theme(axis.title.x = element_blank(), axis.text.y = element_text(size = 15)) + ylab("Cluster 4") + NoLegend()
cluster4.2 <- VlnPlot(subtype, features = c("Atf3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster4.3 <- VlnPlot(subtype, features = c("Zfp36")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster4.4 <- VlnPlot(subtype, features = c("Socs3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
# Cluster 5
cluster5.1 <- VlnPlot(subtype, features = c("Ppbp")) + theme(axis.title.x = element_blank(), axis.text.y = element_text(size = 15), plot.title = element_text(hjust = 0.5)) + labs(title = "Ppbp (Cxcl7)") + ylab("Cluster 5") + NoLegend()
cluster5.2 <- VlnPlot(subtype, features = c("Pf4")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Pf4 (Cxcl4)") + NoLegend()
cluster5.3 <- VlnPlot(subtype, features = c("Adamts4")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
cluster5.4 <- VlnPlot(subtype, features = c("Treml1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
msc.subcluster.patchwork <- (cluster0.1 | cluster0.2 | cluster0.3 | cluster0.4) /
(cluster1.1 | cluster1.2 | cluster1.3 | cluster1.4) /
(cluster2.1 | cluster2.2 | cluster2.3 | cluster2.4) /
(cluster3.1 | cluster3.2 | cluster3.3 | cluster3.4) /
(cluster4.1 | cluster4.2 | cluster4.3 | cluster4.4) /
(cluster5.1 | cluster5.2 | cluster5.3 | cluster5.4) + theme(plot.tag = element_text(size = 8))
gt <- patchwork::patchworkGrob(msc.subcluster.patchwork)
pdf("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/MSCOLCs_Subclusters_VlnPlot_SupplementaryFigure5.pdf", width = 18, height = 18)
gridExtra::grid.arrange(gt, left = textGrob("Scaled Expression", gp=gpar(fontsize=20), rot = 90), bottom = textGrob("Subcluster", gp=gpar(fontsize=20)))
dev.off()
```
# Supplementary figure 6 - BMEC subcluster violin plots
```{r}
bmec1 <- VlnPlot(subtype, features = c("Lpl")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Cluster 0") + NoLegend()
bmec2 <- VlnPlot(subtype, features = c("Bmp6")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec3 <- VlnPlot(subtype, features = c("Sparcl1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec4 <- VlnPlot(subtype, features = c("Sparcl1")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Cluster 1") + NoLegend()
bmec5 <- VlnPlot(subtype, features = c("Timp4")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec6 <- VlnPlot(subtype, features = c("Bmp6")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec7 <- VlnPlot(subtype, features = c("Fbln5")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Cluster 2") + NoLegend()
bmec8 <- VlnPlot(subtype, features = c("Sema3g")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec9 <- VlnPlot(subtype, features = c("Sox17")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec10 <- VlnPlot(subtype, features = c("Atf3")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Cluster 3") + NoLegend()
bmec11 <- VlnPlot(subtype, features = c("Btg2")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec12 <- VlnPlot(subtype, features = c("Socs3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec13 <- VlnPlot(subtype, features = c("Vcam1")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Cluster 4") + NoLegend()
bmec14 <- VlnPlot(subtype, features = c("Sema3a")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec15 <- VlnPlot(subtype, features = c("Sele")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec16 <- VlnPlot(subtype, features = c("Cenpf")) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = 20)) + ylab("Cluster 5") + NoLegend()
bmec17 <- VlnPlot(subtype, features = c("Prc1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec18 <- VlnPlot(subtype, features = c("Knl1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
bmec.subcluster.patchwork <- (bmec1 | bmec2 | bmec3) /
(bmec4 | bmec5 | bmec6) /
(bmec7 | bmec8 | bmec9) /
(bmec10 | bmec11 | bmec12) /
(bmec13 | bmec14 | bmec15) /
(bmec16 | bmec17 | bmec18) + theme(plot.tag = element_text(size = 8))
gt <- patchwork::patchworkGrob(bmec.subcluster.patchwork)
pdf("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/BMEC_Subclusters_VlnPlot_SupplementaryFigure6.pdf", width = 12, height = 18)
gridExtra::grid.arrange(gt, left = textGrob("Scaled Expression", gp=gpar(fontsize=20), rot = 90), bottom = textGrob("Subcluster", gp=gpar(fontsize=20)))
dev.off()
```
# MSC/OLC Supplementary Figures - Secreted - Supplementary Figure 7
```{r}
p1.secrete <- VlnPlot(msclin, features = c("Cxcl12")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p2.secrete <- VlnPlot(msclin, features = c("Ppbp")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Ppbp (Cxcl7)") + NoLegend()
p3.secrete <- VlnPlot(msclin, features = c("Pf4")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Pf4 (Cxcl4)") + NoLegend()
p4.secrete <- VlnPlot(msclin, features = c("Tnfsf13b")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Tnfsf13b (Baff)") + NoLegend()
p5.secrete <- VlnPlot(msclin, features = c("Bglap")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p6.secrete <- VlnPlot(msclin, features = c("Spp1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Spp1 (Opn)") + NoLegend()
p7.secrete <- VlnPlot(msclin, features = c("Col1a1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p8.secrete <- VlnPlot(msclin, features = c("Alpl")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p9.secrete <- VlnPlot(msclin, features = c("Lpl")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p10.secrete <- VlnPlot(msclin, features = c("Adipoq")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p11.secrete <- VlnPlot(msclin, features = c("Mgp")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p12.secrete <- VlnPlot(msclin, features = c("Wif1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p13.secrete <- VlnPlot(msclin, features = c("Fgf7")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p14.secrete <- VlnPlot(msclin, features = c("Igf1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p15.secrete <- VlnPlot(msclin, features = c("Il7")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p16.secrete <- VlnPlot(msclin, features = c("Tnfsf11")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Tnfsf11 (Rankl)") + NoLegend()
p17.secrete <- VlnPlot(msclin, features = c("Tgfb1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p18.secrete <- VlnPlot(msclin, features = c("Tgfb3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p19.secrete <- VlnPlot(msclin, features = c("Sp7")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p20.secrete <- VlnPlot(msclin, features = c("Vegfa")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
secrete.patchwork <- (p1.secrete | p2.secrete | p3.secrete | p4.secrete) /
(p5.secrete | p6.secrete | p7.secrete | p8.secrete) /
(p9.secrete | p10.secrete | p11.secrete | p12.secrete) /
(p13.secrete | p14.secrete | p15.secrete | p16.secrete) /
(p17.secrete | p18.secrete | p19.secrete | p20.secrete) + theme(plot.tag = element_text(size = 8))
gt <- patchwork::patchworkGrob(secrete.patchwork)
pdf("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/MSCOLCs_SecretedMolecules_VlnPlot_ConditionSplit_SupplementaryFigure8.pdf", width = 12, height = 15)
gridExtra::grid.arrange(gt, left = textGrob("Scaled Expression", gp=gpar(fontsize=24), rot = 90), bottom = textGrob("Subcluster", gp=gpar(fontsize=24)))
dev.off()
```
# MSC/OLC Supplementary Figures - Receptors - Supplementary Figure 8
```{r}
library(patchwork)
library(grid)
p1.recep <- VlnPlot(subtype, features = c("Lepr")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p2.recep <- VlnPlot(subtype, features = c("Tgfbr1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p3.recep <- VlnPlot(subtype, features = c("Tgfbr2")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p4.recep <- VlnPlot(subtype, features = c("Tgfbr3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p5.recep <- VlnPlot(subtype, features = c("Tnfrsf1a")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Tnfrsf1a (Tnfr1)") + NoLegend()
p6.recep <- VlnPlot(subtype, features = c("Tnfrsf1b")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), plot.title = element_text(hjust = 0.5)) + labs(title = "Tnfrsf1b (Tnfr2)") + NoLegend()
p7.recep <- VlnPlot(subtype, features = c("Acvr1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p8.recep <- VlnPlot(subtype, features = c("Acvr1b")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p9.recep <- VlnPlot(subtype, features = c("Fgfr1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p10.recep <- VlnPlot(subtype, features = c("Fgfr2")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p11.recep <- VlnPlot(subtype, features = c("Fgfr3")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p12.recep <- VlnPlot(subtype, features = c("Pth1r")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p13.recep <- VlnPlot(subtype, features = c("Bmpr1a")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p14.recep <- VlnPlot(subtype, features = c("Bmpr2")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p15.recep <- VlnPlot(subtype, features = c("Lrp5")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p16.recep <- VlnPlot(subtype, features = c("Lrp6")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p1.adhese <- VlnPlot(subtype, features = c("Vcam1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p2.adhese <- VlnPlot(subtype, features = c("Icam1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p3.adhese <- VlnPlot(subtype, features = c("Jag1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
p4.adhese <- VlnPlot(subtype, features = c("Notch1")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + NoLegend()
receptor.patchwork <- (p1.recep | p2.recep | p3.recep | p4.recep) /
(p5.recep | p6.recep | p7.recep | p8.recep) /
(p9.recep | p10.recep | p11.recep | p12.recep) /
(p13.recep | p14.recep | p15.recep | p16.recep) /
(p1.adhese | p2.adhese | p3.adhese | p4.adhese) + theme(plot.tag = element_text(size = 8))
gt <- patchwork::patchworkGrob(receptor.patchwork)
pdf("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/MSCOLCs_ReceptorAdhesionMolecules_VlnPlot_ConditionSplit_SupplementaryFigure8.pdf", width = 12, height = 16)
gridExtra::grid.arrange(gt, left = textGrob("Scaled Expression", gp=gpar(fontsize=20), rot = 90), bottom = textGrob("Subcluster", gp=gpar(fontsize=20)))
dev.off()
```
# MSC/OLC Supplementary Figures - Adhesion Molecules - Supplementary Figure 10
# BMEC Supplementary Figure Genes
Secreted = Adamts4, Adamts5, Hif1a, Eno1, Tjp1, Vegfa, Sparc, Il15, Tgfb1, Ly96, Flna, Vim, Ywhah, Ywhaz
Receptors = Flt1, Kdr, Flt4, Tnfrsf1a, Aplnr, Itgav, Tlr3, Tlr4
Adhesion = Selp, Sele, Vcam1, Icam1
# Temptest
# Csf3 = Gcsf
# Csf2 = Gmcsf
```{r}
# Secreted
# Receptors
# For immune figure
VlnPlot(subtype, features = c("Ccl5", "Ccl6", "Ccl19", "Cxcl9", "Cxcl10"))
```
# Supplementary Figure 12 - BMEC Secreted Molecules
```{r}
secrete1 <- VlnPlot(subtype, features = c("Vcan")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete2 <- VlnPlot(subtype, features = c("Vegfa")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete3 <- VlnPlot(subtype, features = c("Angpt1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete4 <- VlnPlot(subtype, features = c("Sparc")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete5 <- VlnPlot(subtype, features = c("Tgfb1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete6 <- VlnPlot(subtype, features = c("Ly96")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete7 <- VlnPlot(subtype, features = c("Eno1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete8 <- VlnPlot(subtype, features = c("Hif1a")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete9 <- VlnPlot(subtype, features = c("Tjp1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete10 <- VlnPlot(subtype, features = c("Il15")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete11 <- VlnPlot(subtype, features = c("Bmp4")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete12 <- VlnPlot(subtype, features = c("Egfl7")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete13 <- VlnPlot(subtype, features = c("Flna")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete14 <- VlnPlot(subtype, features = c("Vim")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete15 <- VlnPlot(subtype, features = c("Adamts4")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete16 <- VlnPlot(subtype, features = c("Adamts5")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
secrete.patchwork <- (secrete1 | secrete2 | secrete3 | secrete4) /
(secrete5 | secrete6 | secrete7 | secrete8) /
(secrete9 | secrete10 | secrete11 | secrete12) /
(secrete13 | secrete14 | secrete15 | secrete16) + theme(plot.tag = element_text(size = 8))
gt <- patchwork::patchworkGrob(secrete.patchwork)
pdf("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/BMEC_SecretedMolecules_VlnPlot_SupplementaryFigure12.pdf", width = 16, height = 16)
gridExtra::grid.arrange(gt, left = textGrob("Scaled Expression", gp=gpar(fontsize=16), rot = 90), bottom = textGrob("Subcluster", gp=gpar(fontsize=16)))
dev.off()
```
# Supplementary Figure 13 - Receptor Molecules
```{r}
receptor1 <- VlnPlot(subtype, features = c("Flt1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + labs(title = "Flt (Vegfr-1)") + NoLegend()
receptor2 <- VlnPlot(subtype, features = c("Kdr")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + labs(title = "Kdr (Vegfr-2)") + NoLegend()
receptor3 <- VlnPlot(subtype, features = c("Flt4")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + labs(title = "Flt4 (Vegfr-4)") + NoLegend()
receptor4 <- VlnPlot(subtype, features = c("Tnfrsf1a")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + labs(title = "Tnfrsf1a (Tnfr1)") + NoLegend()
receptor5 <- VlnPlot(subtype, features = c("Jag1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor6 <- VlnPlot(subtype, features = c("Notch1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor7 <- VlnPlot(subtype, features = c("Ifnar1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor8 <- VlnPlot(subtype, features = c("Ifngr1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor9 <- VlnPlot(subtype, features = c("Tlr3")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor10 <- VlnPlot(subtype, features = c("Tlr4")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor11 <- VlnPlot(subtype, features = c("Itgav")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor12 <- VlnPlot(subtype, features = c("Aplnr")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
adhese1 <- VlnPlot(subtype, features = c("Selp")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
adhese2 <- VlnPlot(subtype, features = c("Sele")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
adhese3 <- VlnPlot(subtype, features = c("Vcam1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
adhese4 <- VlnPlot(subtype, features = c("Icam1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
receptor.patchwork <- (receptor1 | receptor2 | receptor3 | receptor4) /
(receptor5 | receptor6 | receptor7 | receptor8) /
(receptor9 | receptor10 | receptor11 | receptor12) /
(adhese1 | adhese2 | adhese3 | adhese4) + theme(plot.tag = element_text(size = 8))
gt <- patchwork::patchworkGrob(receptor.patchwork)
pdf("/Users/gagled01/morganLab/single-cell/5TG_Mouse_Rerun/BMEC_ReceptorAdheseMolecules_VlnPlot_SupplementaryFigure13.pdf", width = 16, height = 16)
gridExtra::grid.arrange(gt, left = textGrob("Scaled Expression", gp=gpar(fontsize=16), rot = 90), bottom = textGrob("Subcluster", gp=gpar(fontsize=16)))
dev.off()
```
# Supplementary Figure 14 - Proinflammatory Cytokines in BMECs
```{r}
cytokine1 <- VlnPlot(subtype, features = c("Il1b")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine2 <- VlnPlot(subtype, features = c("Il6")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine3 <- VlnPlot(subtype, features = c("Il6st")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine4 <- VlnPlot(subtype, features = c("Il11")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine5 <- VlnPlot(subtype, features = c("Il15")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine6 <- VlnPlot(subtype, features = c("Ccl2")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine7 <- VlnPlot(subtype, features = c("Ccl5")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine8 <- VlnPlot(subtype, features = c("Ccl6")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine9 <- VlnPlot(subtype, features = c("Ccl19")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine10 <- VlnPlot(subtype, features = c("Cxcl1")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine11 <- VlnPlot(subtype, features = c("Cxcl9")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()
cytokine12 <- VlnPlot(subtype, features = c("Cxcl10")) + theme(axis.title.x = element_blank(),
axis.title.y = element_blank()) + NoLegend()