R语言笔记：群体药动学数据探索

用到的包

library(dplyr)
library(ggplot2)
library(gridExtra)

加载资源

source("D:\\工作文档\\R\\col_function.r")

设置工作目录

setwd("C:\\Users\\Administrator.ADMIN-20170618T\\Documents\\demo-data\\PPK\\iv infusion 3cp")

读取数据

#read data----
SDTAB<-read.table("SDTAB1",sep="",skip=1,header = TRUE) 
PKdata<-read.csv("MonkeyPK.csv",header=T,skip=2)

过滤数据

#filter data----
PKdata<-filter(MKPK,MDV==0)
PKdata<-filter(MKPK,C!="C")
INDFIT_PK5<-filter(INDFIT_PK,TIME>829)

单位和分类因子

#add unit----
MKPK$DOSE[MKPK$DOSE==0.5]<-"0.5 mg"
#data group----
MKPK$DOSE_f<-factor(MKPK$DOSE,levels=c("0.5 mg","1.5 mg"))

求均值方差等

#Conc Mean Profile-----
ConcvsTIME<-summarise(group_by(MKPKSAD,TIME,DOSE_f),
                      mean=mean(CONC),
                      sd=sd(CONC),
                      n=sum(!is.na(CONC)),
                      se=sd/sqrt(n))

#---
  ylim(0,500)+
  xlim(0,1200)+
  scale_y_log10()+
  facet_wrap(~DOSE_f,ncol=3)+
  facet_wrap(~ID,ncol=7)+
  guides(color=FALSE)+

  legend.text = element_blank()  
  legend.position="none"
  scale_y_log10(breaks=c(c(0.1,1,10,100,1000)),
              labels=c(0.1,1,10,100,1000))
  scale_x_continuous(breaks=c(c(168,336,504,672,840,1008,1176,1344,1512,1680,1848)),
  labels=c("1","2","3","4","5","6","7","8","9","10","11"))
  scale_y_continuous(limits = c(0,800),
                     breaks = seq(0,800,200))+
    scale_x_continuous(limits = c(2040,2160),
                       breaks = seq(2040,2160,24))+
    scale_colour_manual(name="",
                        breaks=c("10 mg","20 mg","40 mg","10~40 mg"),
    scale_colour_hue(labels=c("0.6 mg/kg","1.2 mg/kg","2 mg/kg","3 mg/kg","4 mg/kg","4.5 mg/kg","5.3 mg/kg","7.1 mg/kg","8 mg/kg","9 mg/kg","16 mg/kg","44.5 mg/kg"))+                       values=c("#ED0000CC","#42B540FF","#00468BCC","black")) +  

#----
CONCSADvsTIME<-
  ggplot(data=ConcvsTIME)+
  geom_point(aes(x=TIME,y=mean,group=factor(DOSE_f),color=factor(DOSE_f)))+
  geom_errorbar(aes(x=TIME,ymin=mean-se,ymax=mean+se,color=factor(DOSE_f),group=factor(DOSE_f)),width=0.5,size=0.7)+
  geom_line(aes(x=TIME,y=mean,color=factor(DOSE_f),group=factor(DOSE_f)),size=0.7)+
  labs(color="",shape="")+
  xlab("Time (h)")+ylab("绝对OD值")+
  # facet_wrap(~DOSE_f)+
  theme_test()+
  theme(axis.text=element_text(size=14,color="black"),
        # axis.text.y=element_text(angle = 90,hjust=0.5),
        axis.title =element_text(size=14),
        panel.border = element_rect(colour = "black", fill=NA, size=0.5))
CONCSADvsTIME
ggsave("CONCSADvsTIME.jpeg", CONCSADvsTIME, width = 6, height = 3)


#----
INDFIT_PK2<-filter(INDFIT_PK,NMT<169)
INDFIT_PK3<-filter(INDFIT_PK,NMT>839)
INDFIT_PK<-ggplot()+
  geom_line(data=INDFIT_PK2,aes(x=NMT,y=mean,color=factor(DOSE_f),group=DOSE_f),size=0.7)+
  geom_line(data=INDFIT_PK3,aes(x=NMT,y=mean,color=factor(DOSE_f),group=DOSE_f),size=0.7)+
  geom_point(data=INDFIT_PK,aes(x=NMT,y=mean,color=factor(DOSE_f)))+
  # geom_errorbar(data=INDFIT_PK,aes(x=NMT,ymin=mean-se,ymax=mean+se,color=factor(DOSE_f)),width=0.4,size=0.7)+
  labs(color="",shape="")+
  xlab("Time(h)")+ylab("Concentration (ug/mL)")+
  # xlim(0,1200)+
  # ylim(0,500)+
  # scale_shape_manual(values = c(4:10))+
  theme_test()+
  theme(axis.text=element_text(size=14,color="black"),
        axis.text.y=element_text(angle = 90,hjust=0.5),
        axis.title =element_text(size=14),
        panel.border = element_rect(colour = "black", fill=NA, size=0.5))
INDFIT_PK
ggsave("CONCprofile.jpeg", INDFIT_PK, width = 6, height = 4)


#----
ConcvsTIME<-filter(ConcvsTIME,TIME!=0)
CONCSADvsTIME3<-
  ggplot(data=filter(MKPKSAD,TIME!=0))+
  geom_point(aes(x=TIME,y=CONC,group=factor(ID),color=factor(DOSE_f)),size=1)+
  geom_line(aes(x=TIME,y=CONC,group=factor(ID),color=factor(DOSE_f)),size=0.5)+
  labs(color="",shape="")+
  xlab("Time (h)")+ylab("Concentration (渭g/mL)")+
  facet_wrap(~DOSE_f,ncol=3)+
  theme_test()+
  theme(axis.text=element_text(size=12,color="black"),
        # axis.text.y=element_text(angle = 90,hjust=0.5),
        axis.title =element_text(size=12),
        panel.border = element_rect(colour = "black", fill=NA, size=0.5),
        legend.position="none")
CONCSADvsTIME3
ggsave("CONCSADvsTIMEGROUP.jpeg", CONCSADvsTIME3, width = 6, height = 3)

#CONC----
INDFIT_PK<-EPOPKMAD1
INDFIT_PK4<-filter(INDFIT_PK,TIME<169)
INDFIT_PK5<-filter(INDFIT_PK,TIME>829)
NDFIT_PK<-ggplot()+
  geom_line(data=INDFIT_PK4,aes(x=TIME,y=CONC,group=DOSE_f,color=factor(DOSE_f)))+
  geom_line(data=INDFIT_PK5,aes(x=TIME,y=CONC,group=DOSE_f,color=factor(DOSE_f)))+
  geom_point(data=INDFIT_PK,aes(x=TIME,y=CONC,color=factor(DOSE_f)),shape=21,fill=NA)+
  facet_wrap(~ID,ncol=7)+
  xlab("\nTime after Dose (h)")+ylab("Concentration (ug/mL)\n")+
  guides(color=FALSE)+
  theme_test()+
  theme(axis.text=element_text(size=10,color="black"),
        # axis.text.y=element_text(angle = 90,hjust=0.5),
        axis.title =element_text(size=14),
        panel.border = element_rect(colour = "black", fill=NA, size=0.5),
        strip.background = element_rect(fill="lightblue",colour = NA),
        strip.text = element_text(size = 12))
NDFIT_PK
ggsave("CONCIDprofile.jpeg", NDFIT_PK, width = 14, height = 8)