Significant test for Yanli

library(readxl)
library(dplyr)
library(DescTools)
library(ggpubr)

da<-read_xlsx("e:/Data_YL.xlsx",2)%>%
  mutate(Group=factor(Group))

for(hh in unique(da$Time)){
  
#perform Dunnett's Test
df<-da%>%
  filter(Time==hh)
a<-DunnettTest(x=df$Value, g=df$Group,control = "N",conf.level=0.95)
  
# print(ggqqplot(df$Value))
# print(gghistogram(df$Value, 
#           main = paste0("Histogram plot of data for ",hh),
#           xlab = "value"))

# Normal distribution test (if p>0.05, then data is normally distributed)
print(shapiro.test(df$Value))


# Comparison of each group against base-mean
compare_means(Value ~ Group,  data = df, ref.group = "N",
              method = "t.test")

# Visualize
sig<-ggboxplot(df, x = "Group", y = "Value",
          color = "Group", palette = "jco")+
  stat_compare_means(method = "anova",vjust = 5)+      # Add global p-value
  stat_compare_means(label = "p.signif", method = "t.test",
                     ref.group = "N")                  # Pairwise comparison against "N"


print(hh)
print(a)
print(sig)
}

    Shapiro-Wilk normality test

data:  df$Value
W = 0.90894, p-value = 0.2068

[1] "12 hpi"

  Dunnett's test for comparing several treatments with a control :  
    95% family-wise confidence level

$N
                  diff      lwr.ci   upr.ci   pval    
anti-IL0-N       1.755  0.34041268 3.169587 0.0199 *  
anti-TNF-α-N     1.160 -0.25458732 2.574587 0.1042    
anti-TNF-α/IL0-N 2.055  0.64041268 3.469587 0.0095 ** 
IL0-N            0.550 -0.86458732 1.964587 0.5881    
TNF-α-N          1.390 -0.02458732 2.804587 0.0533 .  

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1


    Shapiro-Wilk normality test

data:  df$Value
W = 0.93449, p-value = 0.4301

[1] "24 hpi"

  Dunnett's test for comparing several treatments with a control :  
    95% family-wise confidence level

$N
                  diff    lwr.ci   upr.ci   pval    
anti-IL0-N       2.820  1.045859 4.594141 0.0058 ** 
anti-TNF-α-N     1.025 -0.749141 2.799141 0.2875    
anti-TNF-α/IL0-N 0.990 -0.784141 2.764141 0.3113    
IL0-N            1.430 -0.344141 3.204141 0.1103    
TNF-α-N          2.440  0.665859 4.214141 0.0124 *  

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1


    Shapiro-Wilk normality test

data:  df$Value
W = 0.94785, p-value = 0.6058

[1] "48 hpi"

  Dunnett's test for comparing several treatments with a control :  
    95% family-wise confidence level

$N
                   diff     lwr.ci     upr.ci   pval    
anti-IL0-N        2.715 -0.4479162  5.8779162 0.0885 .  
anti-TNF-α-N     -2.240 -5.4029162  0.9229162 0.1667    
anti-TNF-α/IL0-N -5.440 -8.6029162 -2.2770838 0.0042 ** 
IL0-N            -2.255 -5.4179162  0.9079162 0.1633    
TNF-α-N           1.805 -1.3579162  4.9679162 0.2959    

---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1