图使用ggplot2

Question

我在尝试使用ggplot2包时遇到了麻烦。我得到的所有图表都是空的

ggplot(data=dataa,aes(x=Description, y=RPKM,fill=Condition)) + 
  geom_bar(position="dodge",stat="identity")

dataa是一个更大的数据框架，如下所示：

Description Tissue  Condition   RPKM
re           brain  obese       34
re1          brain  Fit         23
re2          brain  Slim        67

知道我做错了什么？

我拥有的真实数据：

Description Tissue  Condition   RPKM 
peptidase Brain Obese   0.5
protein Brain   Obese   1.4 
Glucagon    Brain   Fit 0.06 
kinase  Brain   Fit 0.9 
transporter Brain   Obese   4.8 
Secretogran Brain   Slim    87.2 

脚本：

tissues<-factor(unique(RPKMl123upslim$Tissue)) 
for (n in 1:6) { 
    i=c(0,108,216,324,432,540) 
    #datos<-data.frame(RPKMl123upslim[(i[n]+1):(i[n]+108),]) 
    View(datos) 
    ggplot(data=datos,aes(x=Description, y=Expression,fill=Condition)) + 
        geom_bar(position="dodge",stat="identity", colour="black",las=2) 

    path100<-file.path("pajarito",paste("Lupslimrpkm_",tissues[n],".jpg", sep=" ")) 
    jpeg(file=path100) 
    dev.off() 
} 

- Roberto Carlos 2天前

Answer 1

library(ggplot2)
dataa <- data.frame(Description =c("re","re1","re2")
          ,Condition=c("Obese","Fit","Slim"),RPKM=c(34,23,67))

ggplot(data=dataa,aes(x=Description, y=RPKM,fill=Condition))+ 
         geom_bar(position="dodge",stat="identity")`

这就是我得到的

Answer 2

感谢您的帮助，现在我想分享有效的代码：

 dev.set(dev.prev()) 
#dev.new(width=10, height=12)
 path100<-file.path("D:","final.results",paste("skin005",".png", sep=" "))
 png(file=path100, width=1000, height=10000, res=100)
plot(1:100)
attach(skin005RPKMS) #previous data frame with all information
q<-skin005RPKMS[(Skin.Obese > Skin.Fit) & (Skin.Obese > Skin.Slim),]
colnames(q)<-c("Description","Skin.Slim","Skin.Fit","Skin.Obese")
q1<-melt(q,id.vars="Description") #variable contain the different condition    of the experiment and value the data.
p <- ggplot(q1, aes(y=Description,x=variable))+ geom_tile(aes(fill=value)) +   scale_fill_gradientn(colours=c("white","azure2","yellow","blue","orchid","orange red","red","black"), values=rescale(c(0,1,10,50,100,500,1000,4500)),  guide="colorbar") + xlab("Condition") + ylab("Genes")
print(p)
dev.off()