01
1、 加载包,读取数据
library(ggpubr)library(tidyverse)library(ggprism)
k82 <- readxl::read_xlsx("cck8/cck82.xlsx")
> k82# A tibble: 5 × 7 `0` `0.5` `1` `10` `15` `25` `50` <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>1 3.06 3.44 3.59 3.53 3.22 3.39 0.4952 3.43 3.01 2.98 3.19 3.13 2.66 0.6093 3.29 3.43 3.33 2.83 3.10 2.43 0.1534 3.35 3.57 3.60 3.56 3.21 2.47 0.0965 3.48 2.91 2.91 3.35 2.63 1.75 0.227
2、 数据预处理
k82_long <- k82%>% gather(key = Concentration ,value = 'long' )
k8_much <- k82_long%>% mutate(`Cell Viability` = unlist(lapply(k82_long$`long` , function(x){ as.numeric(x)/3.3224 })))
3、 绘图
library(MetBrewer)
isfahan <- MetBrewer::met.brewer("Isfahan1")length(isfahan)
ggline(k8_much, x = "Concentration", y = 'Cell Viability', ylim =c(0,1.2), xlab = "Concentration(mM)", add = c("mean_sd"), # color = "steelblue", color = met.brewer("Renoir")[8],
ggtheme = theme_prism(base_size = 14))
4、 简单折线图的绘制
df1 =data.frame(dose = c(0.5,1,1.5),len = c(4.2,5,6))# 构建数据框
## dose len## 1 D0.5 4.2## 2 D1 10.0## 3 D2 29.5# Basic plotggline(df1,x = "dose",y ="len")