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3.1 corelation - Copy.R
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library(tidyverse)
library(viridis)
library(ggplot2)
library(ggpubr)
library(ggridges)
library(gridExtra)
library(Unicode)
covid_fig5 <-covid %>%
mutate(log_il2 = log(il2), log_il6 = log(il6), log_il8 = log(il8),
log_il10 =log(il10), log_e2 =log(e2) , log_c4 = log(c4) , log_tnf = log(tnf))
## corelation
# & il6 < 600
# & il8 < 200
fig5_il6 <- covid %>% select(severity_char, il6) %>% filter(!is.na(il6) ) %>% mutate(grp = "il6" ) %>% rename(value=il6)
fig5_il8 <- covid %>% select(severity_char, il8) %>% filter(!is.na(il8) ) %>% mutate(grp = "il8" ) %>% rename(value=il8)
fig5_il81 <- fig5_il8 %>% filter(!is.na(severity_char)) %>%
mutate(severity_char1 = if_else(severity_char =="Non-severe", "1. Non-severe", "2. severe" ) )
fig5_c4 <- covid %>% select(severity_char, c4) %>% filter(!is.na(c4) ) %>% mutate(grp = "c4" ) %>% rename(value=c4)
fig5_il2 <- covid %>% select(severity_char, il2) %>% filter(!is.na(il2) ) %>% mutate(grp = "il2" ) %>% rename(value=il2)
fig5 <- rbind(fig5_il6, fig5_il8, fig5_c4, fig5_il2)
mean_fig5 <- fig5 %>% select(severity_char, grp, value) %>% group_by(severity_char, grp) %>%
mutate( value = mean(value) ) %>% distinct()
mean_il6 <- mean_fig5 %>% filter(grp == "il6")
mean_il8 <- mean_fig5 %>% filter(grp == "il8")
mean_c4 <- mean_fig5 %>% filter(grp == "c4")
mean_il2 <- mean_fig5 %>% filter(grp == "il2")
p_il6 <- wilcox.test(value ~ severity_char,data=fig5_il6)
p_il6 <- p_il6$p.value
p_il6 <- if_else ( as.numeric(p_il6)< 0.01, " < 0.01", paste0("= " , round(as.numeric(p_il6), digits = 2 )) )
windowsFonts(Times=windowsFont("Arial"))
icu2_pce_il6 <- icu2 %>% filter(!is.na(il6) & !is.na(pce)) %>% select( pce, il6) %>%
mutate(pce_char = if_else(pce ==0, "No", "Yes"))
mean_pce_il6 <- icu2_pce_il6 %>% filter(!is.na(il6)) %>% select( pce_char, il6) %>%
group_by(pce_char) %>% summarise(value = mean(il6))
p_pce_il6 <- wilcox.test(il6 ~ pce_char,data=icu2_pce_il6)
p_pce_il6 <- p_pce_il6$p.value
p_pce_il6 <- if_else ( as.numeric(p_pce_il6)< 0.01, " < 0.01", paste0( round(as.numeric(p_pce_il6), digits = 2 )) )
#
# fig_il6 <- ggplot()+
# ggplot(data= fig5_il6, aes(x=severity_char, y=value)) +
# geom_jitter(colour = I("BLACK"))
#
#
# geom_point(pch = 21, position = position_jitterdodge())
# ggdotplot(fig5_il6, x = "severity_char", y = "value",
# color = "BLACK", palette = "jco") +
# theme_bw(base_size = 25)
fig_il6 <- ggplot()+
geom_jitter(aes(pce_char, il6) , data = icu2_pce_il6, #alpha=0.5 ,#
position = position_jitter(width = 0.15))+
geom_jitter(aes(severity_char, value ), data = fig5_il6, colour = I("BLACK") , #alpha=0.5 #
position = position_jitter(width = 0.15))+
scale_y_continuous(breaks=seq(0,300,50) ) +
ylim(0, 300) +
geom_crossbar(data=mean_il6,aes(x=severity_char,ymin=value, ymax=value,y=value,group=severity_char), width = 0.5) +
geom_crossbar(data=mean_pce_il6,aes(x=pce_char,ymin=value, ymax=value,y=value,group=pce_char), width = 0.5) +
# annotate("text", x = 1.4, y = 285, size=7, label="italic(p) == 0.04", parse=TRUE) +
annotate("text", x = 1.4, y = 285, size=7, label = "paste(italic(p) , \" = 0.040\")", parse = TRUE) +
annotate("text", x = 3.7, y = 285, size=7, label = "paste(italic(p) , \" < 0.0001\")", parse = TRUE) +
# annotate("text", x = 3.7, y = 285, size=7, label="italic(p) < 0.0001", parse=TRUE) +
scale_x_discrete(limits=c("Non-severe", "severe", "Yes" , "No") ) +
theme_bw(base_size = 22) +
labs(
x = "Disease severity Composite endpoint",
y = "IL6")
fig_il6
# tiff("output/fig_severity_il6.tiff", units="in", width=6, height=4.5, res=300)
# fig_il6
# dev.off()
# setEPS()
# postscript("output/fig_severity_il6.eps")
# fig_il6
# dev.off()
#
# fig_log_il6 <- ggplot()+
# geom_jitter(aes(severity_char, log(value) ), data = fig5_il6, colour = I("BLACK") , alpha=0.5 ,
# position = position_jitter(width = 0.15))+
# scale_y_continuous(breaks=seq(0,3,1) ) +
# ylim(0, 10) +
# geom_crossbar(data=mean_il6,aes(x=severity_char,ymin=value, ymax=value,y=value,group=severity_char), width = 0.5) +
# annotate("text", label = p_il6, x = 0.7, y = 9, size=6) +
# theme_bw(base_size = 20) +
# labs(
# x = "Disease severity",
# y = "Log(IL6)")
icu2_pce_il8 <- icu2 %>% filter(!is.na(il8) & !is.na(pce)) %>% select( pce, il8) %>%
mutate(pce_char = if_else(pce ==0, "No", "Yes"))
mean_pce_il8 <- icu2_pce_il8 %>% filter(!is.na(il8)) %>% select( pce_char, il8) %>%
group_by(pce_char) %>% summarise(value = mean(il8))
p_pce_il8 <- wilcox.test(il8 ~ pce_char,data=icu2_pce_il8)
p_pce_il8 <- p_pce_il8$p.value
p_pce_il8 <- if_else ( as.numeric(p_pce_il8)< 0.01, " < 0.01", paste0( round(as.numeric(p_pce_il8), digits = 2 )) )
p_il8 <- wilcox.test(value ~ severity_char,data=fig5_il8)
p_il8 <- p_il8$p.value
p_il8 <- if_else ( as.numeric(p_il8)< 0.01, " < 0.01", paste0( round(as.numeric(p_il8), digits = 2 )) )
icu2_pce_il8$pce_char <- factor(icu2_pce_il8$pce_char, levels=c("No", "Yes"))
# fig5_il8$severity_char <- factor(fig5_il8$severity_char, levels=c("Non-severe", "Severe"))
fig_il8 <- ggplot()+
geom_jitter(aes(pce_char, il8) , data = icu2_pce_il8, #alpha=0.5 ,
position = position_jitter(width = 0.15))+
geom_jitter(aes(severity_char, value) , data = fig5_il8, #alpha=0.5 ,
position = position_jitter(width = 0.15))+
ylim(0, 300) +
scale_x_discrete(limits=c("Non-severe", "severe", "Yes" , "No") ) +
geom_crossbar(data=mean_il8,aes(x=severity_char,ymin=value, ymax=value,y=value,group=severity_char), width = 0.5) +
geom_crossbar(data=mean_pce_il8,aes(x=pce_char,ymin=value, ymax=value,y=value,group=pce_char), width = 0.5) +
# annotate("text", label = p_il8, x = 1.5, y = 100, size=6) +
annotate("text", x = 1.4, y = 285, size=7, label="italic(p) == 0.033", parse=TRUE) +
annotate("text", x = 3.7, y = 285, size=7, label="italic(p) == 0.00017", parse=TRUE) +
geom_text(x = 14.25, # Set the position of the text to always be at '14.25'
hjust = 0,
size = 8) +
theme_bw(base_size = 22) +
labs(
x = "Disease severity Composite endpoint",
y = "IL8")
# tiff("output/fig_severity_il8.tiff", units="in", width=6, height=4.5, res=300)
# fig_il8
# dev.off()
#################################################################################################3
icu2_pce_il2 <- icu2 %>% filter(!is.na(il2) & !is.na(pce)) %>% select( pce, il2, il6, il8) %>%
mutate(pce_char = if_else(pce ==0, "No", "Yes"))
icu2_pce_il2$pce <- as.factor(icu2_pce_il2$pce)
mean_pce_il2 <- icu2_pce_il2 %>% filter(!is.na(il2)) %>% select( pce_char, il2) %>%
group_by(pce_char) %>% summarise(value = mean(il2))
p_pce_il2 <- wilcox.test(il2 ~ pce_char,data=icu2_pce_il2)
p_pce_il2 <- p_pce_il2$p.value
p_pce_il2 <- if_else ( as.numeric(p_pce_il2)< 0.01, " < 0.01", paste0( round(as.numeric(p_pce_il2), digits = 2 )) )
fig_pce_il2 <- ggplot()+
geom_jitter(aes(pce_char, il2) , data = icu2_pce_il2, #alpha=0.5 ,
position = position_jitter(width = 0.15))+
ylim(0, 3000) +
scale_x_discrete(limits=c("Yes" , "No") ) +
geom_crossbar(data=mean_pce_il2,aes(x=pce_char,ymin=value, ymax=value,y=value,group=pce_char), width = 0.5) +
# annotate("text", label = p_il8, x = 1.5, y = 100, size=6) +
annotate("text", x = 0.8, y = 2800, size=7, label="italic(p) == 0.0091", parse=TRUE) +
geom_text(x = 14.25, # Set the position of the text to always be at '14.25'
hjust = 0,
size = 8) +
theme_bw(base_size = 25) +
labs(
x = "Composite endpoint",
y = "IL2R")
# shapiro.test(icu2_pce_il2$il2 )
#######################################################################################################
#### Scatter plot for IL2,6,8,10,TNF AND E2
####
#######################################################################################################
aa <- covid_fig5 %>% filter(cycle ==1) %>% select(c3,e2 ) %>% filter(!is.na(c3) & !is.na(e2))
#
# ggscatter(aa, x = "c3", y = "e2", add = "reg.line", cor.method = "pearson" ) +
# stat_cor(
# aes(label = paste(..r.label.., ..p.label.., sep = "~`,`~")),
# # label.x = 3,
# label.x.npc = 0.40,
# label.y.npc = 0.9, hjust = 0, size = 7
# ) +
# theme_bw() +
# labs(title=sprintf( "Correlation between %s / %s",tit,lab2 ),
# x = lab1,
# y = lab2)+
# theme_bw(base_size = 25)
covid_fig5 <-covid %>%
mutate(log_il2 = log(il2), log_il6 = log(il6), log_il8 = log(il8),
log_il10 =log(il10), log_e2 =log(e2) , log_c4 = log(c4) , log_tnf = log(tnf))
windowsFonts(Times=windowsFont("Arial"))
scatter1 <- function(var1, var2, lab1, lab2, yellow , tit) {
if (yellow == TRUE ) {
covid_fig5_ <- covid_fig5 %>% filter(cycle ==2)
} else {
covid_fig5_ <- covid_fig5 %>% filter(cycle ==1)
}
ggscatter(covid_fig5_, x = var1, y = var2, add = "reg.line", cor.method = "pearson" ) +
stat_cor(
aes(label = paste(..r.label.., ..p.label.., sep = "~`,`~")),
# label.x = 3,
label.x.npc = 0.40,
label.y.npc = 0.9, hjust = 0, size = 7
) +
theme_bw() +
labs(title=sprintf( "Correlation between %s / %s",tit,lab2 ),
x = lab1,
y = lab2)+
theme_bw(base_size = 25)
}
# cor(aa$c3, aa$e2, method = "pearson", use = "complete.obs")
# covid_fig5_ <- covid_fig5 %>% filter(cycle ==2)
##############il6
il6 <- scatter1("e2", "il6", "E2 (In luteal phase)", "IL6", TRUE, "E2" )
il6 <- il6 + font("title", size = 22)
# tiff("output/FIG5_corpus_il6.tiff" , units="in", width=6, height=3.5, res=300)
# il6
# dev.off()
# font("subtitle", size = 10, color = "orange")+
# font("caption", size = 10, color = "orange")+
# font("xlab", size = 12, color = "blue")+
# font("ylab", size = 12, color = "#993333")+
# font("xy.text", size = 12, color = "gray", face = "bold")
##############il8
il8 <- scatter1("e2", "il8", "E2 (In luteal phase)", "IL8", TRUE, "E2" )
il8 <- il8 + font("title", size = 22)
# tiff("output/FIG5_corpus_il8.tiff" , units="in", width=6, height=3.5, res=300)
# il8
# dev.off()
##############il2
il2 <- scatter1("e2", "il2", "E2 (In luteal phase)", "IL2R", TRUE, "E2" )
il2 <- il2 + font("title", size = 22)
# tiff("output/FIG5_corpus_il2.tiff" , units="in", width=6, height=3.5, res=300)
# il2
# dev.off()
windowsFonts(Times=windowsFont("Arial"))
##############TNF
tnf <- scatter1("e2", "tnf", "E2 (In luteal phase)", paste("TNF", expression("\u03B1") , sep=""), TRUE, "E2" )
tnf <- tnf + font("title", size = 22)
# tiff("output/FIG5_corpus_tnf.tiff" , units="in", width=6, height=3.5, res=300)
# tnf
# dev.off()
#
# tit_tnf <- expression(paste("Correlation between E2 aaa / TNF", "\u03B1"), sep = "")
#
# covid_fig5_ <- covid_fig5 %>% filter(cycle ==2)
# tnf <- ggscatter(covid_fig5_, x ="e2", y = "tnf", add = "reg.line", cor.method = "spearman" ) +
# stat_cor(
# aes(label = paste(..r.label.., ..p.label.., sep = "~`,`~")),
# # label.x = 3,
# label.x.npc = 0.40,
# label.y.npc = 0.9, hjust = 0, size = 7) +
# theme_bw() +
# labs(title= tit_tnf,
# x = "E2 (In luteal phase)",
# y = "TNF")+
# theme_bw(base_size = 15)
#
# tiff("output/FIG5_corpus_tnf.tiff" , units="in", width=6, height=3.5, res=300)
# tnf
# dev.off()
##############C3
# format_pval <- function(pval){
# pval <- scales::pvalue(pval, accuracy= 0.0001, add_p = TRUE)
# gsub(pattern = "(=|<)", replacement = " \\1 ", x = pval)
# }
windowsFonts(Times=windowsFont("Arial"))
c3 <- ggscatter(E2andC3, x = "e2", y = "c3", add = "reg.line", cor.method = "pearson" ) +
# stat_cor(
#
# # aes( label = paste(..r.label.., ..p.label.., sep = "~`,`~")),
# label.x.npc = 0.40,
# label.y.npc = 0.9, hjust = 0, size = 7
# ) +
theme_bw() +
labs(title="Correlation between E2 / C3" ,
x = "E2 (In follicular phase)",
y = "C3")+
theme_bw(base_size = 25) +
# annotate("text", x = 240, y = 1.2, size=7, label = "italic(R) == -0.65, italic(p) == =0.030", parse = TRUE)
# annotate("text", x = 240, y = 1.2, size=7, label="paste(italic(R) italic(p) == 0.0091 )", parse=TRUE)
annotate("text", x = 380, y = 1.15, size=7, label = "paste(italic(R) , \"= -0.65, \", italic(p) , \" = 0.030\")", parse = TRUE)
c3 <- c3 + font("title", size = 22)
# tiff("output/FIG5_folli_C3.tiff" , units="in", width=6, height=3.5, res=300)
# c3
# dev.off();
## create a blank plot
f_blank <- ggplot() + theme_void()
tiff("output/fig_severity.tiff", units="in", width=27, height=9, res=300)
ggarrange(fig_il6, fig_il8, fig_pce_il2, c3,il6, il8, il2, tnf,
labels = c("A", "B", "C", "D" , "E", "F", "G" ,"H" ),
ncol = 4, nrow = 2, font.label = list(size = 25, color = "black") , align = "hv")
dev.off()
ggarrange(fig_il6, fig_il8, fig_pce_il2, c3,il6, il8, il2, tnf,
labels = c("A", "B", "C", "D" , "E", "F", "G" ,"H" ),
ncol = 4, nrow = 2, font.label = list(size = 25, color = "black") , align = "hv")
ggsave("output/fig_severity.eps", width = 27, height = 9, units = "in", dpi = 300)
options(OutDec="\xB7")
pdf(file = "output/fig_severity.pdf", # The directory you want to save the file in
width = 27, # The width of the plot in inches
height = 9) # The height of the plot in inches
ggarrange(fig_il6, fig_il8, fig_pce_il2, c3,il6, il8, il2, tnf,
labels = c("A", "B", "C", "D" , "E", "F", "G" ,"H" ),
ncol = 4, nrow = 2, font.label = list(size = 25, color = "black") , align = "hv")
dev.off()
# setEPS()
# postscript("whatever.eps")
# plot(rnorm(100), main="Hey Some Data")
# dev.off()