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fig.2d_Multi_species_TSPO_espression_box_plot.R
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library(ggplot2)
library(dplyr)
library(DESeq2)
library(patchwork)
load("meta.analysis.tspo/E-GEOD-19315.eset.RData")
dim(E.GEOD.19315.eset)
col_idx <- which(pData(E.GEOD.19315.eset)$Treatment %in% c("untreated", "lipopolysaccharide"))
row_idx <- which(fData(E.GEOD.19315.eset)$V4 == "ENSG00000100300")
exprs(E.GEOD.19315.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.19315",
simulation = pData(E.GEOD.19315.eset)$Treatment[col_idx],
duration = "6h",
species = "Human",
exprs = exprs(E.GEOD.19315.eset)[row_idx, col_idx],
logFC = "log2FC=-0.11",
padj = "p.adj=0.759")
dt <- tmp
load("multi_species_tspo_expression/E-MTAB-7572_human/E-MTAB-7572.dds.rdata")
dim(dds)
plotCounts(dds, gene = "TSPO", intgroup = "Treatment",
normalized = T, transform = F, returnData = T)
col_idx <- which(colData(dds)$Treatment %in% c("none_24", "lipopolysaccharide_24"))
row_idx <- which(rownames(dds) == "TSPO")
counts(dds, normalized = T)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.MTAB.7572",
simulation = colData(dds)$Treatment[col_idx],
duration = "24h",
species = "Human",
exprs = log2(counts(dds, normalized = T)[row_idx, col_idx]),
logFC = "log2FC=-0.65",
padj = "p.adj=2.81e-11")
dt <- rbind(dt, tmp)
load("meta.analysis.tspo.mouse/E-GEOD-15610.eset.RData")
dim(E.GEOD.15610.eset)
col_idx <- which(pData(E.GEOD.15610.eset)$Treatment %in% c("untreated", "LPSstimulated"))
row_idx <- which(fData(E.GEOD.15610.eset)$Gene_Name == "Tspo")
exprs(E.GEOD.15610.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.15610",
simulation = pData(E.GEOD.15610.eset)$Treatment[col_idx],
duration = "4h",
species = "Mouse",
exprs = exprs(E.GEOD.15610.eset)[row_idx, col_idx],
logFC = "log2FC=0.69",
padj = "p.adj=0.0417")
dt <- rbind(dt, tmp)
load("meta.analysis.tspo.mouse/E-GEOD-53986.eset.RData")
dim(E.GEOD.53986.eset)
col_idx <- which(pData(E.GEOD.53986.eset)$Treatment %in% c("untreated", "LPS"))
row_idx <- which(fData(E.GEOD.53986.eset)$Gene_Name == "Tspo")
exprs(E.GEOD.53986.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.53986",
simulation = pData(E.GEOD.53986.eset)$Treatment[col_idx],
duration = "24h",
species = "Mouse",
exprs = exprs(E.GEOD.53986.eset)[row_idx, col_idx],
logFC = "log2FC=2.04",
padj = "p.adj=9.17e-06")
dt <- rbind(dt, tmp)
load("multi_species_tspo_expression/E-MEXP-3469_Rat_macrophage_LPS_prashant/E.MEXP.3469.eset.rdata")
dim(E.MEXP.3469.eset)
col_idx <- which(pData(E.MEXP.3469.eset)$Treatment %in%
c("none.0hour", "lipopolysaccharide.4hour"))
row_idx <- which(rownames(E.MEXP.3469.eset) == "Tspo")
exprs(E.MEXP.3469.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.MEXP.3469",
simulation = pData(E.MEXP.3469.eset)$Treatment[col_idx],
duration = "4h",
species = "Rat",
exprs = exprs(E.MEXP.3469.eset)[row_idx, col_idx],
logFC = "log2FC=0.21",
padj = "p.adj=0.0373")
dt <- rbind(dt, tmp)
col_idx <- which(pData(E.MEXP.3469.eset)$Treatment %in%
c("none.0hour", "lipopolysaccharide.8hour"))
row_idx <- which(rownames(E.MEXP.3469.eset) == "Tspo")
exprs(E.MEXP.3469.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.MEXP.3469",
simulation = pData(E.MEXP.3469.eset)$Treatment[col_idx],
duration = "8h",
species = "Rat",
exprs = exprs(E.MEXP.3469.eset)[row_idx, col_idx],
logFC = "log2FC=1.23",
padj = "p.adj=1.92e-08")
dt <- rbind(dt, tmp)
load("multi_species_tspo_expression/E-GEOD-6353_rat/E.GEOD.6353.eset.rdata")
dim(E.GEOD.6353.eset)
col_idx <- which(pData(E.GEOD.6353.eset)$Treatment %in%
c("Control", "IFNg"))
row_idx <- which(fData(E.GEOD.6353.eset)$Composite.Element.Name == "J05122_at")
exprs(E.GEOD.6353.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.6353",
simulation = pData(E.GEOD.6353.eset)$Treatment[col_idx],
duration = "16h",
species = "Rat",
exprs = exprs(E.GEOD.6353.eset)[row_idx, col_idx],
logFC = "log2FC=1.53",
padj = "p.adj=0.0015")
dt <- rbind(dt, tmp)
load("multi_species_tspo_expression/E-GEOD-59263_rabbit/E.GEOD.59263.4h.eset.rdata")
dim(E.GEOD.59263.4h.eset)
col_idx <- which(pData(E.GEOD.59263.4h.eset)$FactorValue..STIMULATION. %in%
c("control", "LPS"))
row_idx <- which(fData(E.GEOD.59263.4h.eset)$Reporter.Identifier == "A_04_P038882")
exprs(E.GEOD.59263.4h.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.59263",
simulation = pData(E.GEOD.59263.4h.eset)$FactorValue..STIMULATION.[col_idx],
duration = "4h",
species = "Rabbit",
exprs = exprs(E.GEOD.59263.4h.eset)[row_idx, col_idx],
logFC = "log2FC=-0.94",
padj = "p.adj=0.139")
dt <- rbind(dt, tmp)
load("multi_species_tspo_expression/E-GEOD-59263_rabbit/E.GEOD.59263.24h.eset.rdata")
dim(E.GEOD.59263.24h.eset)
col_idx <- which(pData(E.GEOD.59263.24h.eset)$FactorValue..STIMULATION. %in%
c("control", "LPS"))
row_idx <- which(fData(E.GEOD.59263.24h.eset)$Reporter.Identifier == "A_04_P038882")
exprs(E.GEOD.59263.24h.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.59263",
simulation = pData(E.GEOD.59263.24h.eset)$FactorValue..STIMULATION.[col_idx],
duration = "24h",
species = "Rabbit",
exprs = exprs(E.GEOD.59263.24h.eset)[row_idx, col_idx],
logFC = "log2FC=-0.07",
padj = "p.adj=0.9318")
dt <- rbind(dt, tmp)
load("multi_species_tspo_expression/GSE71037_sheep/GSE71037_dds.rda")
dim(dds)
plotCounts(dds, gene = "PBR", intgroup = "treatment",
normalized = T, transform = F, returnData = T)
col_idx <- which(colData(dds)$treatment %in% c("Saline", "LPS"))
row_idx <- which(rownames(dds) == "PBR")
counts(dds, normalized = T)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "GSE71037",
simulation = colData(dds)$treatment[col_idx],
duration = "6h",
species = "Sheep",
exprs = log2(counts(dds, normalized = T)[row_idx, col_idx]),
logFC = "log2FC=0.08",
padj = "p.adj=0.9826")
dt <- rbind(dt, tmp)
load("multi_species_tspo_expression/E-GEOD-30956_pig/E-GEOD-30956_eset.rdata")
dim(E.GEOD.30956.eset)
col_idx <- which(pData(E.GEOD.30956.eset)$FactorValue..TIMEPOINT. %in%
c("0h", "7h"))
row_idx <- which(fData(E.GEOD.30956.eset)$Composite.Element.Name == "Ssc.5936.1.A1_a_at")
exprs(E.GEOD.30956.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.30956",
simulation = pData(E.GEOD.30956.eset)$FactorValue..TIMEPOINT.[col_idx],
duration = "7h",
species = "Pig",
exprs = exprs(E.GEOD.30956.eset)[row_idx, col_idx],
logFC = "log2FC=0.12",
padj = "p.adj=0.9993")
dt <- rbind(dt, tmp)
col_idx <- which(pData(E.GEOD.30956.eset)$FactorValue..TIMEPOINT. %in%
c("0h", "24h"))
row_idx <- which(fData(E.GEOD.30956.eset)$Composite.Element.Name == "Ssc.5936.1.A1_a_at")
exprs(E.GEOD.30956.eset)[row_idx, col_idx]
tmp <- data.frame(dataset_id = "E.GEOD.30956",
simulation = pData(E.GEOD.30956.eset)$FactorValue..TIMEPOINT.[col_idx],
duration = "24h",
species = "Pig",
exprs = exprs(E.GEOD.30956.eset)[row_idx, col_idx],
logFC = "log2FC=0.04",
padj = "p.adj=1")
dt <- rbind(dt, tmp)
TSPO_expression <- dt %>%
mutate(species = factor(species,
levels = c("Human", "Pig", "Sheep", "Rabbit", "Mouse", "Rat" )),
species_duration = paste(species, duration,
sep = " "),
species_duration = factor(species_duration,
levels = c("Human 6h",
"Human 24h",
"Pig 2h",
"Pig 7h",
"Pig 24h",
"Cow 2h",
"Sheep 6h",
"Rabbit 4h",
"Rabbit 24h",
"Mouse 4h",
"Mouse 24h",
"Rat 2h",
"Rat 4h",
"Rat 8h",
"Rat 16h"
)),
treatment = case_when(simulation %in% c("untreated", "none_24", "none.0hour",
"Control", "control", "Saline", "0h") ~ "Naive",
TRUE ~ "Stimulated"),
group = paste(species_duration, treatment, sep = " "),
treatment_duration = paste(treatment, duration, sep = " "),
duration = factor(duration, levels = c("4h", "6h", "7h", "8h", "16h", "24h"))
) %>%
group_by(group) %>%
mutate(Mean = mean(exprs)) %>%
ungroup %>%
group_by(species_duration) %>%
mutate(exprs_scaled = exprs/unique(Mean[treatment == "Naive"])) %>%
ungroup() %>%
mutate(label_sig = gsub("p.adj=", "", padj) %>% as.numeric()) %>%
mutate_at(., "label_sig", ~case_when(. <= 0.001 ~ "***",
. <= 0.01 ~ "**",
. <= 0.05 ~ "*",
. > 0.05 ~ " ")
)
ann_text <- TSPO_expression %>%
select(c(species, duration, treatment, exprs, exprs_scaled, label_sig)) %>%
group_by(species, duration) %>%
mutate(y_val = max(exprs_scaled)+ 0.05) %>%
ungroup() %>%
select(-c(exprs, exprs_scaled)) %>%
distinct() %>%
group_by(species) %>%
mutate(x = as.numeric(factor(duration))) %>%
ungroup() %>%
mutate(xmin = ifelse(label_sig == " ", NA, x - 0.2),
xmax = ifelse(label_sig == " ", NA, x + 0.2),
group1 = "Naive",
group2 = "Stimulated")
palette_choice <- paletteer::paletteer_d("ggsci::nrc_npg")
p1 <- ggplot(TSPO_expression)+
geom_boxplot(aes(x = duration, y = exprs_scaled, fill = treatment),
color = "black", outlier.colour = "white", width = 1)+
geom_point(aes(x = duration, y = exprs_scaled, fill = treatment),
position = position_dodge(1),
shape = 21, size = 2, show.legend = F)+
ylab("Normalized relative expression")+
geom_hline(yintercept = 1, linetype = "dashed")+
xlab("")+
scale_color_manual(name = NULL, values = palette_choice[c(2,1)],
aesthetics = c("colour", "fill")) +
theme_bw() +
theme(axis.text.x = element_text(color = "black", size = 16),
axis.text.y = element_text(color = "black", size = 16),
axis.title = element_text(color = "black", size = 18),
strip.text = element_text(color = "black", size = 18),
legend.text = element_text(color = "black", size = 18),
panel.border = element_rect(color = "black", fill = NA),
panel.grid = element_blank()) +
facet_grid(~species, scales = "free_x", space = "free") +
scale_y_continuous(limits = c(0.5, 1.5),
expand = c(0, 0)) +
ggpubr::stat_pvalue_manual(data = ann_text, label = "label_sig", y.position = "y_val", tip.length = 0.01)
ggsave("multi_species_tspo_expression/TSPO expression in multiple species box plot.png",
units = "in", width = 16, height = 4, dpi = 300, bg = "white")