Question

我是新手R用户。我试图根据Tarralidar's work使用等效线图编写分析药物协同作用的代码我不确定我是否正确使用，所以我尝试将药物与自己的药物结合起来并应用于我的代码。

这是我的数据

Master.data <- rbind(data.frame(Drug = "T1", Dose = c(1,0.5,0.25,0.125), Effect = c(0.5987,0.2382,0.0602,-0.0027), DrugID = "A"),
                 data.frame(Drug = "T2", Dose = c(1,0.5,0.25,0.125), Effect = c(0.5987,0.2382,0.0602,-0.0027), DrugID = "B"),
                 data.frame(Drug = "Combo", Dose = c(2,1,0.5,0.25), Effect = c(0.7774,0.5987,0.2382,0.0602), DrugID = "Combo")
                 )

我使用这些来配合药物与drc包，并使用ggplot2绘制结果代码。

library("ggplot2")
library("drc")
#Divide data into drug group
A <- subset(Master.data, DrugID == "A")
B <- subset(Master.data, DrugID == "B")
Combo <- subset(Master.data, DrugID == "Combo")
##########################################
#Dose response curve of Drug A
A.model <- drm(Effect~Dose, data = A, fct = LL.4())
CA <- ED(A.model,50)[1,1]
q <- data.frame(Value = coef(A.model))
p1 <- data.frame(S = seq(0.05, max(Master.data$Dose), length.out = 100))
p1 <- rbind(p1,CA)
p1$v <- predict(A.model, newdata = p1)
p1$Drug <- A[1,'Drug']
#########################################
#Dose response curve of Drug B
B.model <- drm(Effect~Dose, data = B, fct = LL.4())
CB <- ED(B.model,50)[1,1]
p <- data.frame(Value = coef(B.model))
p2 <- data.frame(S = seq(0.05, max(Master.data$Dose), length.out = 100))
p2 <- rbind(p2, CB)
p2$v <- predict(B.model, newdata = p2)
p2$Drug <- B[1,'Drug']
#########################################
#Dose response curve of Combo
Combo.model <- drm(Effect~Dose, data = Combo, fct = LL.4())
ComboED50 <- ED(Combo.model,50)[1,1]
p3 <- data.frame(S = seq(0.05, max(Master.data$Dose), length.out = 100))
p3 <- rbind(p3,ComboED50)
p3$v <- predict(Combo.model, newdata = p3)
p3$Drug <- Combo[1,'Drug']
##########################################
#Plot dose response for p1,p2,p3 
p <- rbind(p1,p2,p3)
ggplot(p, aes(x = S, y = v, col = Drug)) + geom_line()+
labs(title = "Dose response curve") + xlab("Dose uM (log scale)") + ylab("Growth inhibition") +
scale_x_log10() +
ylim(min(p$v),1) +
geom_point(data = subset(Master.data,Dose != 0), aes(x = Dose, y = Effect))
##########################################

其中产生合理的剂量 - 反应曲线。

现在我定义进一步计算所需的值。

#######Create dose combination#########
R <- max(A$Dose)/max(B$Dose) ## Ratio of drug A and B -> R=A/B
EA <- max(A$Effect) ## Maximum effect of drug A -> EA
EB <- max(B$Effect) ## Maximum effect of drug B -> EB
CA <- ED(A.model,50)[1,1] ## Half maximum effect of drug A
CB <- ED(B.model,50)[1,1] ## Half maximum effect of drug B

创建用于绘制药物组合点的表格

Combo.table <- data.frame(Combo$Dose)
Combo.table <- rbind(Combo.table,0)
for (i in c(1:99)) {
 Combo.table <- rbind(Combo.table,ED(Combo.model,i)[1,1])
}
Combo.table$A <- (Combo.table[,1]*R)/(R+1)
Combo.table$B <- Combo.table[,1]/(1+R)
colnames(Combo.table) <- c("Combo","A","B")

使用此功能，我创建了等效线图，可以应用于药物组合，每种药物具有不同的最大效果。

Iso <- function(i) {
         Isolobe <- data.frame(seq(0,ED(A.model,i)[1,1],length.out = 100))
         Isolobe <- rbind(Isolobe,CA)
         colnames(Isolobe) <- "Dose.a"
         Isolobe$Dose.b <- ED(B.model,i)[1,1]-(CB/(((EB/EA)*(1+(CA/Isolobe$Dose.a)))-1))

         ggplot(Isolobe, aes(x = Dose.a,y = Dose.b)) +
         geom_line() +
         xlab(A[1,"Drug"]) + ylab(B[1,"Drug"]) + labs(title = "Isobologram", subtitle = "Dose in uM") +
         geom_point(data = subset(Combo.table,Combo==ED(Combo.model,i)[1,1]), aes(x = A,y = B))
}

有了这一切，我执行了这个功能。

Iso(50)

应该为组合的ED50创建Isobologram并绘制药物A，B点的分数。

问题来自这个样本，我故意使用相同的药物A，B数据和组合数据来自一层更多相同的数据。这应该指出添加剂系上的药物部分。显然，它不是。

底线是我做错了什么？

药物组合的等效线图

0 个答案: