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theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(TYPE~REPI,scales = "free_y",nrow =1, ncol = 4 )
print(w19blood)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 4,useDingbats=FALSE)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="red",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(TYPE~REPI,scales = "free_y",nrow =1, ncol = 4 )
print(w19blood)
blood_W19_freq_data<- rbind(blood_W19_freq_data1,blood_W19_freq_data2)
blood_W19_freq_data$TYPE<- c("Cherry")
wtblood_W19_freq_data$TYPE<- c("EGFP")
blood_W19_freq_data<- rbind(blood_W19_freq_data,wtblood_W19_freq_data)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="red",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(TYPE~REPI,scales = "free_y",nrow =1, ncol = 4 )
print(w19blood)
blood_W19_freq_data<- rbind(blood_W19_freq_data1,blood_W19_freq_data2)
blood_W19_freq_data$TYPE<- c("mCherry")
wtblood_W19_freq_data$TYPE<- c("EGFP")
blood_W19_freq_data<- rbind(blood_W19_freq_data,wtblood_W19_freq_data)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="red",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(TYPE~REPI,scales = "free_y",nrow =1, ncol = 4 )
print(w19blood)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_grid(TYPE~REPI,scales = "free")#,nrow =2, ncol = 4 )
print(w19blood)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_grid(TYPE~REPI,scales = "free_x")#,nrow =2, ncol = 4 )
print(w19blood)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(TYPE~REPI,scales = "free_x")#,nrow =2, ncol = 4 )
print(w19blood)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(TYPE~REPI,scales = "free_xy")#,nrow =2, ncol = 4 )
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(TYPE~REPI,scales = "free")#,nrow =2, ncol = 4 )
print(w19blood)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
View(wtblood_W19_freq_data)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~REPI,scales = "free")#,nrow =2, ncol = 4 )
print(w19blood)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 4,useDingbats=FALSE)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 4,useDingbats=FALSE)
View(mh5_freq_data)
allrepli_h5_wt_corrplot<- rbind(mh5_freq_data,mwt_freq_data)
View(allrepli_h5_wt_corrplot)
allrepli_h5_wt_corrplot$TYPE<- c("mCherry")
allrepli_h5_wt_corrplot[grepl("WT",allrepli_h5_wt_corrplot$CLONE_ID),"TYPE"]<- "EGFP"
View(allrepli_h5_wt_corrplot)
ggc<- ggplot(allrepli_h5_wt_corrplot,aes(x=R1,y=R2,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.0001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.0001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~TIME,scales = "free_y",nrow =1, ncol = 4 )
print(ggc)
ggc<- ggplot(allrepli_h5_wt_corrplot,aes(x=R1,y=R2,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~TIME,scales = "free_y",nrow =1, ncol = 4 )
print(ggc)
ggsave("m584H5WT_replicate_corplot.pdf",ggc,device = "pdf",width = 11,height = 3,useDingbats=FALSE)
ggsave("m584H5WT_replicate_corplot.pdf",ggc,device = "pdf",width = 12,height = 3,useDingbats=FALSE)
ggc<- ggplot(allrepli_h5_wt_corrplot,aes(x=R1,y=R2,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~TIME,scales = "free_y",nrow =2, ncol = 2 )
print(ggc)
ggc<- ggplot(allrepli_h5_wt_corrplot,aes(x=R1,y=R2,color=TYPE,fill=TYPE))+geom_point(size=2)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~TIME,scales = "free",nrow =2, ncol = 2 )
print(ggc)
ggsave("m584H5WT_replicate_corplot.pdf",ggc,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
ggc<- ggplot(allrepli_h5_wt_corrplot,aes(x=R1,y=R2,color=TYPE,fill=TYPE))+geom_point(size=3)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~TIME,scales = "free",nrow =2, ncol = 2 )
print(ggc)
ggsave("m584H5WT_replicate_corplot.pdf",ggc,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
ggc<- ggplot(allrepli_h5_wt_corrplot,aes(x=R1,y=R2,color=TYPE,fill=TYPE))+geom_point(size=3,alpha=0.5)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~TIME,scales = "free",nrow =2, ncol = 2 )
print(ggc)
ggsave("m584H5WT_replicate_corplot.pdf",ggc,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
w19blood<- ggplot(blood_W19_freq_data,aes(W19,PB,color=TYPE,fill=TYPE))+geom_point(size=3,alpha=0.7)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~REPI,scales = "free")#,nrow =2, ncol = 4 )
print(w19blood)
ggsave("m584_blood_PB_corplot.pdf",w19blood,device = "pdf",width = 8,height = 4,useDingbats=FALSE)
ggc<- ggplot(allrepli_h5_wt_corrplot,aes(x=R1,y=R2,color=TYPE,fill=TYPE))+geom_point(size=3,alpha=0.7)+#stat_ellipse(color="red",size=1)+
geom_abline(size=1,color="blue",alpha=0.5)+
scale_color_manual(values = c("darkgreen","darkred"))+
scale_fill_manual(values = c("darkgreen","darkred"))+
theme_classic2()+theme(panel.border = element_blank(),#element_rect(colour = "black",size = 1),
strip.background = element_blank(),
panel.grid.major=element_blank(),
axis.ticks.y = element_line(colour = "black", size = 0.5),
#axis.ticks.x = element_blank(),
strip.text.x = element_text(size=12,face="bold"),
#strip.text.y = element_blank(),
panel.background = element_blank())+
theme(axis.text.x = element_text(color="black",size=16,face = "bold"))+
theme(axis.text.y = element_text(color="black",size=16,face = "bold"))+
theme(legend.position="none")+
scale_y_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
scale_x_log10(limit=c(0.00001,5),breaks = c(0.001,0.01,0.1,1),labels =c(0.001,0.01,0.1,1))+
theme(panel.spacing.x = unit(0.5, "lines"))+
facet_wrap(~TIME,scales = "free",nrow =2, ncol = 2 )
print(ggc)
ggsave("m584H5WT_replicate_corplot.pdf",ggc,device = "pdf",width = 8,height = 8,useDingbats=FALSE)
setwd("C:/Users/gajendra/Dropbox/Chen_Lab/2018/MDA_mosue_data/m603")
source('C:/Users/gajendra/Dropbox/Chen_Lab/2018/MDA_mosue_data/m603/analysis_script_m603.R')
source('C:/Users/gajendra/Dropbox/Chen_Lab/2018/MDA_mosue_data/m603/analysis_script_m603.R')
matrix(c(7,8,9,10,11,12),nrow = 2,ncol = 3)
matrix(c(7,8,9,10,11,12),nrow = 2,ncol = 3)[,3]
median(c(0.95,0.95,0.91,0.86,0.8,0.84,0.98,0.98))
avg(c(0.95,0.95,0.91,0.86,0.8,0.84,0.98,0.98))
mean(c(0.95,0.95,0.91,0.86,0.8,0.84,0.98,0.98))
mean(c(0.1,0.83,0.08,0.42,0.99,0.99,0.99,0.99,0.93,0.98,0.99,0.97))
median(c(0.1,0.83,0.08,0.42,0.99,0.99,0.99,0.99,0.93,0.98,0.99,0.97))
setwd("~/Dropbox/perltesting")
tcr_data<- read.delim("TCR_data.tsv",header = T,sep = "\t")
View(tcr_data)
row.names(tcr_data)<- tcr_data$X
row.names(tcr_data)<- tcr_data$X
tcr_data<- tcr_data/100
View(tcr_data)
tcr_data<- tcr_data[,-1]/100
View(tcr_data)
tcr_data<- read.delim("TCR_data.tsv",header = T,sep = "\t")
row.names(tcr_data)<- tcr_data$X
tcr_data<- tcr_data[,-1]/100
View(tcr_data)
gtb_clones2<- tcr_data
View(gtb_clones2)
colSums(gtb_clones2)
gtb_clones2$ZeroCount<- c(unname(apply(as.matrix(gtb_clones2[,-1]),1,function(x)sum(x!=0))))
View(gtb_clones2)
gtb_clones2<- tcr_data
gtb_clones2$ZeroCount<- c(unname(apply(as.matrix(gtb_clones2),1,function(x)sum(x!=0))))
View(gtb_clones2)
dataplot1<- data.frame(matrix(nrow = 0,ncol = length(names(gtb_clones[,-1]))))
dataplot1<- data.frame(matrix(nrow = 0,ncol = length(names(gtb_clones))))
dataplot1<- data.frame(matrix(nrow = 0,ncol = length(names(gtb_clones2))))
View(dataplot1)
names(dataplot1)<- names(gtb_clones2)
tempgtb<- gtb_clones2[gtb_clones2$ZeroCount==3]
tempgtb<- gtb_clones2[gtb_clones2$ZeroCount==3,]
tempgtb<- tempgtb[order(tempgtb[,1],decreasing = T),]
dataplot1<- rbind(dataplot1,tempgtb)
View(dataplot1)
View(dataplot1)
tem1<- gtb_clones2[gtb_clones2$ZeroCount==1,-1]
View(tem1)
for(zr1 in c(3,2,1)){
tem4<- tem1[tem1[,zr1]!=0,]
tem4<- tem4[order(tem4[,zr1],decreasing = T),]
dataplot1<- rbind(dataplot1,tem4)
}
temp2<- gtb_clones2[gtb_clones2$ZeroCount==2,-1]
View(temp2)
for(zr in c(2,3)){
tem3<- temp2[temp2[,zr]==0,]
tem3<- tem3[order(tem3[,1],decreasing = T),]
dataplot1<- rbind(dataplot1,tem3)
}
View(dataplot1)
tem3<- temp2[temp2[,1]==0,]
tem3<- tem3[order(tem3[,2],decreasing = T),]
dataplot1<- rbind(dataplot1,tem3)
dataplot1$CLONE_ID<- rownames(dataplot1)
dataplot1$NCID<- paste0("NCID",sprintf("%0.4d",seq(1,length(dataplot1$CLONE_ID))))
dataplot1$COLOR<- rep(brewer.pal(12, "Paired"),length(dataplot1$CLONE_ID)/10)[seq(1,length(dataplot1$CLONE_ID))]
library(RColorBrewer)
dataplot1$COLOR<- rep(brewer.pal(12, "Paired"),length(dataplot1$CLONE_ID)/10)[seq(1,length(dataplot1$CLONE_ID))]
View(dataplot1)
#----
dataplot<- rbind(dataplot,dataplot1)
View(dataplot1)
#----
#dataplot<- rbind(dataplot,dataplot1)
axnames<-data.frame(Org=c("thymus","spleen","mLN"),Axis=c('a1','a3','a2'))
mtem<- melt(dataplot1[,!grepl("Zero",names(dataplot1))])
library(reshape2)
mtem<- melt(dataplot1[,!grepl("Zero",names(dataplot1))])
petaldata<- data.frame(matrix(nrow = 0,ncol = 6))
names(petaldata)<- c('CLONE_ID','axis','value1','value2','COLOR')
for(m in c(1,2,3)){
tem<- mtem[mtem$variable==as.character(axnames$Org[m]),]
tem<- tem[tem$value>0.00,]
tem$value2<- cumsum(tem$value)
tem$value1<- tem$value2-tem$value
tem$axis<- axnames$Axis[m]
#tem<- tem[order(tem$value,decreasing = T)[1:100],]
petaldata<- rbind(petaldata,tem[,c('CLONE_ID','axis','value1','value2','COLOR')])
}
petaldata$COLOR<- sub("#","",petaldata$COLOR)
filenams<- paste0("TCR_petal_data.txt")
write.table(petaldata,filenams,sep = '\t',quote = F,row.names = F,col.names = F)
View(petaldata)
maxval<- data.frame(maxv=c(colSums(bbs_data[,-1])))
maxval<- data.frame(maxv=c(colSums(gtb_clones2)))
maxval$TIS<- rownames(maxval)
View(maxval)
?cor
?rcor
??rcor
library(Hmisc)
#rownames(gtb_clones2)<- gtb_clones2$CLONE_ID
rcorr(gtb_clones2)
#rownames(gtb_clones2)<- gtb_clones2$CLONE_ID
rcorr(matrix(gtb_clones2))
#rownames(gtb_clones2)<- gtb_clones2$CLONE_ID
rcorr(matrix(tcr_data))
View(tcr_data)
matrix(tcr_data)
#rownames(gtb_clones2)<- gtb_clones2$CLONE_ID
rcorr(tcr_data)
#rownames(gtb_clones2)<- gtb_clones2$CLONE_ID
rcor(tcr_data)
#rownames(gtb_clones2)<- gtb_clones2$CLONE_ID
cor(tcr_data)
source('~/Dropbox/perltesting/tcr_data-shaper.R')
View(petaldata)
#rownames(gtb_clones2)<- gtb_clones2$CLONE_ID
cor(tcr_data)
#https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930077/
tcr_data<- read.delim("TCR_data3.txt",header = T,sep = "\t")
source('~/Dropbox/perltesting/tcr_data-shaper.R')
source('~/Dropbox/perltesting/tcr_data-shaper.R')
source('~/Dropbox/perltesting/tcr_data-shaper.R')
source('~/Dropbox/perltesting/tcr_data-shaper.R')
View(gtb_clones2)
source('~/Dropbox/perltesting/tcr_data-shaper.R')
source('~/Dropbox/perltesting/tcr_data-shaper.R')
View(tem1)
View(dataplot1)
View(gtb_clones2)
source('~/Dropbox/perltesting/tcr_data-shaper.R')
source('~/Dropbox/perltesting/tcr_data-shaper.R')
View(dataplot1)
View(tem4)
View(gtb_clones2)
source('~/Dropbox/perltesting/tcr_data-shaper.R')
source('~/Dropbox/perltesting/tcr_data-shaper.R')