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Copy pathUMAPs_and_featurePlots.R
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UMAPs_and_featurePlots.R
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#UMAPs and FeaturePlots
library(singleCellTK)
library(tidyverse)
library(Seurat)
library(scCustomize)
library(gridExtra)
library(EnhancedVolcano)
library(clustree)
#Read in merged.srt
merged.srt <- readRDS("/Users/emilyfitzmeyer/Desktop/scRNAseq_pub/mergeDPI_oldNorm/alldpi_oldNorm_nmn_res0.6.rds")
#rename clusters
new_idents <- c("EC-like-1", "1", "EC-like-2", "ISC/EB", "4", "EC", "EC-like-3", "VM-1", "8", "VM-2", "ISC/EB-prol", "cardia-1", "EE", "cardia-2", "HC-1", "MT", "HC-2", "17", "cardia-prol", "19")
merged.srt <- Rename_Clusters(merged.srt, new_idents = new_idents)
#add cell type info to metadata
ident_num <- c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19")
cell_type <- c("EC-like-1", "1", "EC-like-2", "ISC/EB", "4", "EC", "EC-like-3", "VM-1", "8", "VM-2", "ISC/EB-prol", "cardia-1", "EE", "cardia-2", "HC-1", "MT", "HC-2", "17", "cardia-prol", "19")
tib <- tibble(ident_num, cell_type)
merged.srt <- Add_Sample_Meta(merged.srt, meta_data = tib, join_by_seurat = "seurat_clusters", join_by_meta = "ident_num")
my_levels <- c("VM-2", "VM-1", "MT", "ISC/EB-prol", "ISC/EB", "HC-2", "HC-1", "EE", "EC-like-3", "EC-like-2", "EC-like-1", "EC", "cardia-prol", "cardia-2", "cardia-1", "19", "17", "8", "4", "1")
factor(Idents(merged.srt), levels = my_levels)
Idents(merged.srt) <- factor(Idents(merged.srt), levels = my_levels)
split.srt <- SplitObject(merged.srt, split.by = "dpi")
srt_4dpi <- split.srt$"4dpi"
srt_12dpi<- split.srt$"12dpi"
srt_4dpi <- SplitObject(srt_4dpi, split.by = "condition")
srt_12dpi <- SplitObject(srt_12dpi, split.by = "condition")
#show sample and condition induced impact on cell grouping:
sample_plot_4dpi <- DimPlot(srt_4dpi, reduction = 'umap', group.by = 'sample', pt.size = 0.1) &
theme(axis.text.x = element_text(size = 15)) &
theme(axis.text.y = element_text(size = 15)) &
scale_x_continuous(labels = NULL) &
ggtitle("Sample Grouping") &
labs(x = NULL)
sample_plot_12dpi <- DimPlot(srt_12dpi, reduction = 'umap', group.by = 'sample', pt.size = 0.1) &
theme(axis.text.x = element_text(size = 15)) &
theme(axis.text.y = element_text(size = 15)) &
ggtitle(NULL)
condition_plot_4dpi <- DimPlot(srt_4dpi, reduction = 'umap', group.by = 'condition',
cols = c('deepskyblue', 'salmon'), pt.size = 0.1) &
theme(axis.text.x = element_text(size = 15)) &
theme(axis.text.y = element_text(size = 15)) &
scale_x_continuous(labels = NULL) &
scale_y_continuous(labels = NULL) &
ggtitle("Condition Grouping") &
labs(x = NULL, y = NULL)
condition_plot_12dpi <- DimPlot(srt_12dpi, reduction = 'umap', group.by = 'condition',
cols = c('deepskyblue', 'salmon'), pt.size = 0.1) &
theme(axis.text.x = element_text(size = 15)) &
theme(axis.text.y = element_text(size = 15)) &
scale_y_continuous(labels = NULL) &
ggtitle(NULL) &
labs(y = NULL)
plot <- sample_plot_4dpi + condition_plot_4dpi + sample_plot_12dpi + condition_plot_12dpi + patchwork::plot_layout(ncol = 2)
setwd("/Users/emilyfitzmeyer/Desktop/")
ggsave("batch_plots.png", plot = plot, device = png(), scale = 1, width = 8.5, height = 6.5, dpi = 300)
dev.off()
#plot WNV 5' UTR:
WNV.utr.4dpi.mock <- FeaturePlot(srt_4dpi$mock, features = "nbis-gene-2-utr", pt.size = 0.5, cols = c("grey", "grey")) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
theme(legend.position = 'none') +
scale_x_discrete(labels = 'none') +
ggtitle("Mock") +
labs(x = NULL) +
theme(axis.title.y = element_text(vjust = -2.5))
WNV.utr.4dpi.wnv <- FeaturePlot(srt_4dpi$wnv, features = "nbis-gene-2-utr", pt.size = 0.5) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
theme(legend.position = c(0.92, 0.92)) +
ggtitle("WNV") +
scale_x_discrete(labels = 'none') +
scale_y_discrete(labels = 'none') +
labs(x = NULL, y = NULL)
WNV.utr.12dpi.mock <- FeaturePlot(srt_12dpi$mock, features = "nbis-gene-2-utr", pt.size = 0.5, cols = c("grey", "grey")) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
theme(legend.position = 'none') +
ggtitle(NULL) +
theme(axis.title.y = element_text(vjust = -2.5))
WNV.utr.12dpi.wnv <- FeaturePlot(srt_12dpi$wnv, features = "nbis-gene-2-utr", pt.size = 0.5) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
theme(legend.position = 'none') +
ggtitle(NULL) +
scale_y_discrete(labels = 'none') +
labs(y = NULL)
plot <- WNV.utr.4dpi.mock + WNV.utr.4dpi.wnv + WNV.utr.12dpi.mock + WNV.utr.12dpi.wnv + patchwork::plot_layout(ncol = 2)
setwd("/Users/emilyfitzmeyer/Desktop/")
ggsave("utr_load_featureplots.png", plot = plot, device = png(), scale = 1, width = 7.5, height = 7.5, dpi = 300)
dev.off()
#view cell cycle features__________________________________________________________________________________
#S phase
FeaturePlot(merged.srt, features = c("gene7803", "gene1526", "gene2166", "gene577", "gene9562"))
ggsave("sPhase_bothdpi_plots.png", plot = last_plot(), device = png(), scale = 1, width = 8, height = 10, dpi = 300)
dev.off()
#G2/M phase
FeaturePlot(merged.srt, features = c("gene13155", "gene9499", "gene7697", "gene4233", "gene11073", "gene13413", "gene13452", "gene5102", "gene9506", "gene6438", "gene7563", "gene9947"))
ggsave("g2mPhase_bothdpi_plots.png", plot = last_plot(), device = png(), scale = 1, width = 15, height = 10, dpi = 300)
dev.off()
#view apoptotic genes__________________________________________________________________________________
FeaturePlot(merged.srt, features = c("gene2212", "gene13832", "gene9932", "gene11674", "gene4419", "gene9707", "gene1473", "gene13123", "gene14035"))
ggsave("apoptotic_bothdpi_plots.png", plot = last_plot(), device = png(), scale = 1, width = 12, height = 10, dpi = 300)
dev.off()
#ISC plots
klu_Fplot <- FeaturePlot(merged.srt, features = "gene13104", pt.size = 0.2) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
theme(legend.position = c(0.1, 0.95)) +
# scale_x_continuous(limits = c(-6, 4)) +
# scale_y_continuous(limits = c(-14, -7)) +
theme(legend.text = element_text(size = 17)) +
ggtitle("Klu")
klu_Vplot <- VlnPlot(merged.srt, features = "gene13104") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
labs(x = NULL) +
ggtitle("Klu")
plot <- klu_Fplot + klu_Vplot + patchwork::plot_layout(ncol = 2)
ggsave("klu_bothdpi_plots.png", plot = plot, device = png(), scale = 1, width = 9, height = 5, dpi = 300)
dev.off()
#ISC-prol plots
pcna_Fplot <- FeaturePlot(merged.srt, features = "gene2167", pt.size = 0.5) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_continuous(limits = c(-6, 4), labels = NULL) +
scale_y_continuous(limits = c(-14, -7)) +
theme(legend.position = c(0.9, 0.23)) +
theme(legend.text = element_text(size = 17)) +
theme(legend.position = c(0.85, 0.95)) +
labs(x = NULL) +
ggtitle("PCNA")
pcna_Vplot <- VlnPlot(merged.srt, features = "gene2167") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_discrete(labels = NULL) +
labs(x = NULL) +
ggtitle("PCNA")
aurka_Fplot <- FeaturePlot(merged.srt, features = "gene13413", pt.size = 0.5) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_continuous(limits = c(-6, 4), labels = NULL) +
scale_y_continuous(limits = c(-14, -7)) +
theme(legend.position = c(0.9, 0.23)) +
theme(legend.text = element_text(size = 17)) +
theme(legend.position = 'none') +
labs(x = NULL) +
ggtitle("AURKA")
aurka_Vplot <- VlnPlot(merged.srt, features = "gene13413") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_discrete(labels = NULL) +
labs(x = NULL) +
ggtitle("AURKA")
aurkb_Fplot <- FeaturePlot(merged.srt, features = "gene12926", pt.size = 0.5) +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_continuous(limits = c(-6, 4)) +
scale_y_continuous(limits = c(-14, -7)) +
theme(legend.position = c(0.9, 0.23)) +
theme(legend.text = element_text(size = 17)) +
theme(legend.position = 'none') +
ggtitle("AURKB")
aurkb_Vplot <- VlnPlot(merged.srt, features = "gene12926") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
labs(x = NULL) +
ggtitle("AURKB")
plot <- pcna_Fplot + pcna_Vplot + aurka_Fplot + aurka_Vplot + aurkb_Fplot + aurkb_Vplot + patchwork::plot_layout(ncol = 2)
ggsave("prol_marker_bothdpi_plots.png", plot = plot, device = png(), scale = 1, width = 9, height = 11, dpi = 300)
dev.off()
#PROX1 plots
prox1_Fplot <- FeaturePlot(merged.srt, features = "gene10632") +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
theme(legend.position = c(0.1, 0.95)) +
ggtitle("PROX1")
prox1_Vplot <- VlnPlot(merged.srt, features = "gene10632") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
labs(x = NULL) +
ggtitle("PROX1")
plot <- prox1_Fplot + prox1_Vplot + patchwork::plot_layout(ncol = 2)
ggsave("PROX1_plots_bothdpi.png", plot = last_plot(), device = png(), scale = 1, width = 9, height = 5, dpi = 300)
dev.off()
#VM plots
actb_Fplot <- FeaturePlot(merged.srt, features = "gene2985") +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_continuous(labels = NULL) +
theme(legend.position = c(0.05, 0.95)) +
labs(x = NULL) +
ggtitle("ACTB")
mhc_Fplot <- FeaturePlot(merged.srt, features = "gene11104") +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_continuous(labels = NULL) +
theme(legend.position = 'none') +
labs(x = NULL) +
ggtitle("Mhc/Mhc1")
mlc_Fplot <- FeaturePlot(merged.srt, features = "gene9804") +
theme(axis.text.x = element_text(size = 17)) +
theme(axis.text.y = element_text(size = 17)) +
theme(legend.position = 'none') +
ggtitle("Mlc2")
actb_Vplot <- VlnPlot(merged.srt, features = "gene2985") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_discrete(labels = NULL) +
labs(x = NULL) +
ggtitle("ACTB")
mhc_Vplot <- VlnPlot(merged.srt, features = "gene11104") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
scale_x_discrete(labels = NULL) +
labs(x = NULL) +
ggtitle("Mhc/Mhc1")
mlc2_Vplot <- VlnPlot(merged.srt, features = "gene9804") +
theme(legend.position = 'none') +
theme(axis.text.x = element_text(size = 12)) +
theme(axis.text.y = element_text(size = 17)) +
labs(x = NULL) +
ggtitle("Mlc2")
plot <- actb_Fplot + actb_Vplot + mhc_Fplot + mhc_Vplot + mlc_Fplot + mlc2_Vplot + patchwork::plot_layout(ncol = 2)
ggsave("VM_markers_bothdpi.png", plot = plot, device = png(), scale = 1, width = 9, height = 11, dpi = 300)
dev.off()
#EC plots
FeaturePlot(merged.srt, features = "gene11957")