QC_PCA

```{r QC--PCA}

rm(list=ls())
library(ggplot2)
DIAnn<-read.table("06_protein_matrix/proteotypic/DIAnn_part_ave_KMDR_proteotypic_matrix.txt",header = T,sep = '\t')

DIAnn2<-data.frame(DIAnn[,c(grep("_repB",names(DIAnn)))])

names1<-c((gsub("_repB","",names(DIAnn2))),names(DIAnn2))


DIAnn3<-data.frame(DIAnn[,c(which(names(DIAnn)%in% names1))])

a<-substr(names(DIAnn3),25,40)
names(DIAnn3)<-a
DIAnn4<-data.frame(names(DIAnn3),t(DIAnn3))
DIAnn5<-DIAnn4[order(DIAnn4[,1]),-1]
DIAnn6<-data.frame(t(DIAnn5))

d1 <- data.frame(2^(DIAnn6[,]))


d2 <- data.frame((DIAnn6[,]))

for (i in 1:5) {
  s1<-unlist(d1[,2*i-1])
  s2<-unlist(d1[,2*i])
  
  s3<-unlist(d2[,2*i-1])
  s4<-unlist(d2[,2*i])
  
r <- cor(s1, s2, use = 'pairwise.complete.obs')  


ic1 <- data.frame(s3,s4)
         ha <-  ggplot(ic1, aes(x = s3, y=s4))+
             geom_point(shape=1,size=2,colour="steelblue2")+
             stat_smooth(method=lm, se=FALSE,colour="black",size=0.3)+
             
           labs(y=(names(d2)[2*i]), 
              x=(names(d2)[2*i-1]),
              subtitle=list(paste0("r= ",round(r,3))))+
            
            theme_bw() +
            theme(panel.grid =element_blank())+
            theme(plot.subtitle=element_text(size=30, hjust=0, color="black"))+
            theme(axis.title.x=element_text(size=20, hjust=0.5, color="black"))+
            theme(axis.title.y=element_text(size=20, hjust=0.5, color="black"))
     
         
ggsave(paste0("13_QC/DIAnn_UnLog_QC",names(d2)[2*i-1],".pdf"),ha,width=8,height=8)

}

#######VIOLIN###
library(vioplot)
library(RColorBrewer)
list<-names(DIAnn[,-1])

list2<-gsub("_repB","",list)

DIAnn7<-data.frame(list2,t(2^DIAnn[,-1]))

DIAnn8<-aggregate(DIAnn7[,colnames(DIAnn7)[2:ncol(DIAnn7)]],by=list(DIAnn7$list2),mean,na.rm= TRUE)

DIAnn9<-DIAnn8[order(DIAnn8[,1]),]



df1<-data.frame(t(DIAnn9[,-1]))

names(df1)<-c(as.matrix(DIAnn9[,1]))


df<-data.frame(df1)

nrow<-nrow(df)

ncol<-ncol(df)

for (k in 1:7) {
  


for (i in 1:nrow ) {
  
  x<-as.matrix(df1[i,(3*k-2):(3*k)])
  
  cv<-sd(x)/mean(x)
  
  df[i,ncol+k]<-cv
  
}

}

df2<-df[,c((ncol+1):28)]

names(df2)<-c("K","A1","A2","A3","I1","I2","I3")



d<-names(df2)


nrowdf2<-nrow(df2)

ncoldf2<-ncol(df2)


library(vioplot)

library(RColorBrewer)

df3<-df2

A1<-as.numeric(df3$A1)

A2<-as.numeric(df3$A2)

A3<-as.numeric(df3$A3)
I1<-as.numeric(df3$I1)

I2<-as.numeric(df3$I2)

I3<-as.numeric(df3$I3)

K<-as.numeric(df3$K)

color<-c(brewer.pal(8,"Accent")[1:7])



pdf("13_QC/DIAnn_un_log_violin_biorep.pdf")
a<-vioplot(K,A1,A2,A3,I1,I2,I3,
        areaEqual=FALSE, col=c("seagreen4", "seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
      rectCol=c("seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
     lineCol=c("black", "black", "black", "black", "black", "black", "black"),
    border=c("black","black", "black", "black", "black", "black", "black"),
 names=c( "k"  ,"A1","A2", "A3", "I1", "I2", "I3"),
      main="biological replicates", xlab="model", ylab="CV",plotCentre = "point")


write.table(a,"13_QC/DIAnn_note.txt",sep = "\t")

##########pca###

library(umap)
source("common.R")


library(RColorBrewer)

label1<-substr(DIAnn7[,1],25,27)

label2<-gsub("_","",label1)
label<-substr(label2,1,1)


DIAnn10<-data.frame(label,DIAnn7[,-1])

color <- c("#3678AD","#D6221E","#4DA74A")


drawPCA(DIAnn10,color,rowNormalization = F,colNormalization =T ,strTitle = NULL)

ggsave("13_QC/DIAnn_PCA_allProt.pdf",height = 6,width = 6)


rm(list=ls())
library(ggplot2)
Spec<-read.table("06_protein_matrix/proteotypic/Spec_part_ave_KMDR_proteotypic_matrix.txt",header = T,sep = '\t')

Spec2<-data.frame(Spec[,c(grep("_repB",names(Spec)))])

names1<-c((gsub("_repB","",names(Spec2))),names(Spec2))


Spec3<-data.frame(Spec[,c(which(names(Spec)%in% names1))])

a<-substr(names(Spec3),25,40)
names(Spec3)<-a
Spec4<-data.frame(names(Spec3),t(Spec3))
Spec5<-Spec4[order(Spec4[,1]),-1]
Spec6<-data.frame(t(Spec5))

d1 <- data.frame(2^(Spec6[,]))


d2 <- data.frame((Spec6[,]))

for (i in 1:5) {
  s1<-unlist(d1[,2*i-1])
  s2<-unlist(d1[,2*i])
  
  s3<-unlist(d2[,2*i-1])
  s4<-unlist(d2[,2*i])
  
r <- cor(s1, s2, use = 'pairwise.complete.obs')  


ic1 <- data.frame(s3,s4)
         ha <-  ggplot(ic1, aes(x = s3, y=s4))+
             geom_point(shape=1,size=2,colour="steelblue2")+
             stat_smooth(method=lm, se=FALSE,colour="black",size=0.3)+
             
           labs(y=(names(d2)[2*i]), 
              x=(names(d2)[2*i-1]),
              subtitle=list(paste0("r= ",round(r,3))))+
            
            theme_bw() +
            theme(panel.grid =element_blank())+
            theme(plot.subtitle=element_text(size=30, hjust=0, color="black"))+
            theme(axis.title.x=element_text(size=20, hjust=0.5, color="black"))+
            theme(axis.title.y=element_text(size=20, hjust=0.5, color="black"))
     
         
ggsave(paste0("13_QC/Spec_UnLog_QC",names(d2)[2*i-1],".pdf"),ha,width=8,height=8)

}

#######VIOLIN###
library(vioplot)
library(RColorBrewer)
list<-names(Spec[,-1])

list2<-gsub("_repB","",list)

Spec7<-data.frame(list2,t(2^Spec[,-1]))

Spec8<-aggregate(Spec7[,colnames(Spec7)[2:ncol(Spec7)]],by=list(Spec7$list2),mean,na.rm= TRUE)

Spec9<-Spec8[order(Spec8[,1]),]



df1<-data.frame(t(Spec9[,-1]))

names(df1)<-c(as.matrix(Spec9[,1]))


df<-data.frame(df1)

nrow<-nrow(df)

ncol<-ncol(df)

for (k in 1:7) {
  


for (i in 1:nrow ) {
  
  x<-as.matrix(df1[i,(3*k-2):(3*k)])
  
  cv<-sd(x)/mean(x)
  
  df[i,ncol+k]<-cv
  
}

}

df2<-df[,c((ncol+1):28)]

names(df2)<-c("K","A1","A2","A3","I1","I2","I3")



d<-names(df2)


nrowdf2<-nrow(df2)

ncoldf2<-ncol(df2)


library(vioplot)

library(RColorBrewer)

df3<-df2

A1<-as.numeric(df3$A1)

A2<-as.numeric(df3$A2)

A3<-as.numeric(df3$A3)
I1<-as.numeric(df3$I1)

I2<-as.numeric(df3$I2)

I3<-as.numeric(df3$I3)

K<-as.numeric(df3$K)

color<-c(brewer.pal(8,"Accent")[1:7])



pdf("13_QC/Spec_un_log_violin_biorep.pdf")
a<-vioplot(K,A1,A2,A3,I1,I2,I3,
        areaEqual=FALSE, col=c("seagreen4", "seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
      rectCol=c("seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
     lineCol=c("black", "black", "black", "black", "black", "black", "black"),
    border=c("black","black", "black", "black", "black", "black", "black"),
 names=c( "k"  ,"A1","A2", "A3", "I1", "I2", "I3"),
      main="biological replicates", xlab="model", ylab="CV",plotCentre = "point")



write.table(a,"13_QC/Spec_note.txt",sep = "\t")

##########pca###

library(umap)
source("common.R")


library(RColorBrewer)

label1<-substr(Spec7[,1],25,27)

label2<-gsub("_","",label1)
label<-substr(label2,1,1)


Spec10<-data.frame(label,Spec7[,-1])

color <- c("#3678AD","#D6221E","#4DA74A")


drawPCA(Spec10,color,rowNormalization = F,colNormalization =T ,strTitle = NULL)

ggsave("13_QC/Spec_PCA_allProt.pdf",height = 6,width = 6)




rm(list=ls())
library(ggplot2)
Encyo<-read.table("06_protein_matrix/proteotypic/Encyo_part_ave_KMDR_proteotypic_matrix.txt",header = T,sep = '\t')

Encyo2<-data.frame(Encyo[,c(grep("_repB",names(Encyo)))])

names1<-c((gsub("_repB","",names(Encyo2))),names(Encyo2))


Encyo3<-data.frame(Encyo[,c(which(names(Encyo)%in% names1))])

a<-substr(names(Encyo3),25,40)
names(Encyo3)<-a
Encyo4<-data.frame(names(Encyo3),t(Encyo3))
Encyo5<-Encyo4[order(Encyo4[,1]),-1]
Encyo6<-data.frame(t(Encyo5))

d1 <- data.frame(2^(Encyo6[,]))


d2 <- data.frame((Encyo6[,]))

for (i in 1:5) {
  s1<-unlist(d1[,2*i-1])
  s2<-unlist(d1[,2*i])
  
  s3<-unlist(d2[,2*i-1])
  s4<-unlist(d2[,2*i])
  
r <- cor(s1, s2, use = 'pairwise.complete.obs')  


ic1 <- data.frame(s3,s4)
         ha <-  ggplot(ic1, aes(x = s3, y=s4))+
             geom_point(shape=1,size=2,colour="steelblue2")+
             stat_smooth(method=lm, se=FALSE,colour="black",size=0.3)+
             
           labs(y=(names(d2)[2*i]), 
              x=(names(d2)[2*i-1]),
              subtitle=list(paste0("r= ",round(r,3))))+
            
            theme_bw() +
            theme(panel.grid =element_blank())+
            theme(plot.subtitle=element_text(size=30, hjust=0, color="black"))+
            theme(axis.title.x=element_text(size=20, hjust=0.5, color="black"))+
            theme(axis.title.y=element_text(size=20, hjust=0.5, color="black"))
     
         
ggsave(paste0("13_QC/Encyo_UnLog_QC",names(d2)[2*i-1],".pdf"),ha,width=8,height=8)

}

#######VIOLIN###
library(vioplot)
library(RColorBrewer)
list<-names(Encyo[,-1])

list2<-gsub("_repB","",list)

Encyo7<-data.frame(list2,t(2^Encyo[,-1]))

Encyo8<-aggregate(Encyo7[,colnames(Encyo7)[2:ncol(Encyo7)]],by=list(Encyo7$list2),mean,na.rm= TRUE)

Encyo9<-Encyo8[order(Encyo8[,1]),]



df1<-data.frame(t(Encyo9[,-1]))

names(df1)<-c(as.matrix(Encyo9[,1]))


df<-data.frame(df1)

nrow<-nrow(df)

ncol<-ncol(df)

for (k in 1:7) {
  


for (i in 1:nrow ) {
  
  x<-as.matrix(df1[i,(3*k-2):(3*k)])
  
  cv<-sd(x)/mean(x)
  
  df[i,ncol+k]<-cv
  
}

}

df2<-df[,c((ncol+1):28)]

names(df2)<-c("K","A1","A2","A3","I1","I2","I3")



d<-names(df2)


nrowdf2<-nrow(df2)

ncoldf2<-ncol(df2)


library(vioplot)

library(RColorBrewer)

df3<-df2

A1<-as.numeric(df3$A1)

A2<-as.numeric(df3$A2)

A3<-as.numeric(df3$A3)
I1<-as.numeric(df3$I1)

I2<-as.numeric(df3$I2)

I3<-as.numeric(df3$I3)

K<-as.numeric(df3$K)

color<-c(brewer.pal(8,"Accent")[1:7])



pdf("13_QC/Encyo_un_log_violin_biorep.pdf")
a<-vioplot(K,A1,A2,A3,I1,I2,I3,
        areaEqual=FALSE, col=c("seagreen4", "seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
      rectCol=c("seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
     lineCol=c("black", "black", "black", "black", "black", "black", "black"),
    border=c("black","black", "black", "black", "black", "black", "black"),
 names=c( "k"  ,"A1","A2", "A3", "I1", "I2", "I3"),
      main="biological replicates", xlab="model", ylab="CV",plotCentre = "point")


write.table(a,"13_QC/Encyo_note.txt",sep = "\t")

##########pca###

library(umap)
source("common.R")


library(RColorBrewer)

label1<-substr(Encyo7[,1],25,27)

label2<-gsub("_","",label1)
label<-substr(label2,1,1)


Encyo10<-data.frame(label,Encyo7[,-1])

color <- c("#3678AD","#D6221E","#4DA74A")


drawPCA(Encyo10,color,rowNormalization = F,colNormalization =T ,strTitle = NULL)

ggsave("13_QC/Encyo_PCA_allProt.pdf",height = 6,width = 6)



rm(list=ls())
library(ggplot2)
Openswath<-read.table("06_protein_matrix/proteotypic/Openswath_part_ave_KMDR_proteotypic_matrix.txt",header = T,sep = '\t')

Openswath2<-data.frame(Openswath[,c(grep("_repB",names(Openswath)))])

names1<-c((gsub("_repB","",names(Openswath2))),names(Openswath2))


Openswath3<-data.frame(Openswath[,c(which(names(Openswath)%in% names1))])

a<-substr(names(Openswath3),25,40)
names(Openswath3)<-a
Openswath4<-data.frame(names(Openswath3),t(Openswath3))
Openswath5<-Openswath4[order(Openswath4[,1]),-1]
Openswath6<-data.frame(t(Openswath5))

d1 <- data.frame(2^(Openswath6[,]))


d2 <- data.frame((Openswath6[,]))

for (i in 1:5) {
  s1<-unlist(d1[,2*i-1])
  s2<-unlist(d1[,2*i])
  
  s3<-unlist(d2[,2*i-1])
  s4<-unlist(d2[,2*i])
  
r <- cor(s1, s2, use = 'pairwise.complete.obs')  


ic1 <- data.frame(s3,s4)
         ha <-  ggplot(ic1, aes(x = s3, y=s4))+
             geom_point(shape=1,size=2,colour="steelblue2")+
             stat_smooth(method=lm, se=FALSE,colour="black",size=0.3)+
             
           labs(y=(names(d2)[2*i]), 
              x=(names(d2)[2*i-1]),
              subtitle=list(paste0("r= ",round(r,3))))+
            
            theme_bw() +
            theme(panel.grid =element_blank())+
            theme(plot.subtitle=element_text(size=30, hjust=0, color="black"))+
            theme(axis.title.x=element_text(size=20, hjust=0.5, color="black"))+
            theme(axis.title.y=element_text(size=20, hjust=0.5, color="black"))
     
         
ggsave(paste0("13_QC/Openswath_UnLog_QC",names(d2)[2*i-1],".pdf"),ha,width=8,height=8)

}

#######VIOLIN###
library(vioplot)
library(RColorBrewer)
list<-names(Openswath[,-1])

list2<-gsub("_repB","",list)

Openswath7<-data.frame(list2,t(2^Openswath[,-1]))

Openswath8<-aggregate(Openswath7[,colnames(Openswath7)[2:ncol(Openswath7)]],by=list(Openswath7$list2),mean,na.rm= TRUE)

Openswath9<-Openswath8[order(Openswath8[,1]),]



df1<-data.frame(t(Openswath9[,-1]))

names(df1)<-c(as.matrix(Openswath9[,1]))


df<-data.frame(df1)

nrow<-nrow(df)

ncol<-ncol(df)

for (k in 1:7) {
  


for (i in 1:nrow ) {
  
  x<-as.matrix(df1[i,(3*k-2):(3*k)])
  
  cv<-sd(x)/mean(x)
  
  df[i,ncol+k]<-cv
  
}

}

df2<-df[,c((ncol+1):28)]

names(df2)<-c("K","A1","A2","A3","I1","I2","I3")



d<-names(df2)


nrowdf2<-nrow(df2)

ncoldf2<-ncol(df2)


library(vioplot)

library(RColorBrewer)

df3<-df2

A1<-as.numeric(df3$A1)

A2<-as.numeric(df3$A2)

A3<-as.numeric(df3$A3)
I1<-as.numeric(df3$I1)

I2<-as.numeric(df3$I2)

I3<-as.numeric(df3$I3)

K<-as.numeric(df3$K)

color<-c(brewer.pal(8,"Accent")[1:7])



pdf("13_QC/Openswath_un_log_violin_biorep.pdf")
a<-vioplot(K,A1,A2,A3,I1,I2,I3,
        areaEqual=FALSE, col=c("seagreen4", "seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
      rectCol=c("seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4","seagreen4"),
     lineCol=c("black", "black", "black", "black", "black", "black", "black"),
    border=c("black","black", "black", "black", "black", "black", "black"),
 names=c( "k"  ,"A1","A2", "A3", "I1", "I2", "I3"),
      main="biological replicates", xlab="model", ylab="CV",plotCentre = "point")


write.table(a,"13_QC/Openswath_note.txt",sep = "\t")

##########pca###

library(umap)
source("common.R")


library(RColorBrewer)

label1<-substr(Openswath7[,1],25,27)

label2<-gsub("_","",label1)
label<-substr(label2,1,1)


Openswath10<-data.frame(label,Openswath7[,-1])

color <- c("#3678AD","#D6221E","#4DA74A")


drawPCA(Openswath10,color,rowNormalization = F,colNormalization =T ,strTitle = NULL)

ggsave("13_QC/Openswath_PCA_allProt.pdf",height = 6,width = 6)


```