Main figures
Briana Mittleman
5/30/2020
Last updated: 2020-12-22
Checks: 7 0
Knit directory: Comparative_APA/analysis/
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Unstaged changes:
Modified: analysis/DeandNumPAS.Rmd
Modified: analysis/DirSelectionKhan.Rmd
Modified: analysis/ExploredAPA.Rmd
Modified: analysis/ExploredAPA_DF.Rmd
Modified: analysis/MMExpreiment.Rmd
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Modified: analysis/TotalVNuclearBothSpecies.Rmd
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Modified: analysis/changeMisprimcut.Rmd
Modified: analysis/comp2apaQTLPAS.Rmd
Modified: analysis/correlationPhenos.Rmd
Modified: analysis/dInforContent.Rmd
Modified: analysis/df_QC.Rmd
Modified: analysis/diffExpression.Rmd
Modified: analysis/establishCutoffs.Rmd
Modified: analysis/incorporateQTLsAncestral.Rmd
Modified: analysis/index.Rmd
Modified: analysis/infoContent.Rmd
Modified: analysis/investigatePantro5.Rmd
Modified: analysis/mRNADecay.Rmd
Modified: analysis/miRNAanalysis.Rmd
Modified: analysis/multiMap.Rmd
Modified: analysis/phastCon.Rmd
Modified: analysis/pol2.Rmd
Modified: analysis/speciesSpecific.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/mainFigures.Rmd) and HTML (docs/mainFigures.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 26bf7e4 | brimittleman | 2020-12-22 | add spearmans |
| html | 8f57bf7 | brimittleman | 2020-07-28 | Build site. |
| Rmd | 7f8f707 | brimittleman | 2020-07-28 | fix typos, add log2 |
| html | f9e1b34 | brimittleman | 2020-07-25 | Build site. |
| Rmd | dc22f17 | brimittleman | 2020-07-25 | edits for manuscrit updates 7.25 |
| html | 8cf8116 | brimittleman | 2020-06-30 | Build site. |
| Rmd | 40aae53 | brimittleman | 2020-06-30 | fix main fig typos |
| html | f31a5a0 | brimittleman | 2020-06-26 | Build site. |
| Rmd | eeccce8 | brimittleman | 2020-06-26 | remore last 3 |
| html | 6c4190e | brimittleman | 2020-06-11 | Build site. |
| Rmd | faf8902 | brimittleman | 2020-06-11 | fix typos |
| html | a438fc1 | brimittleman | 2020-05-31 | Build site. |
| Rmd | 2c88fe0 | brimittleman | 2020-05-31 | fig 5 and 6 |
| html | c1c2047 | brimittleman | 2020-05-31 | Build site. |
| Rmd | 033290c | brimittleman | 2020-05-31 | add main figures 1-4 |
I would like to plot all of the main figures in one R markdown with cowplot. I will save the data frames in the other files as rds objects then load them here.
library(cowplot)
********************************************************Note: As of version 1.0.0, cowplot does not change the default ggplot2 theme anymore. To recover the previous behavior, execute:
theme_set(theme_cowplot())********************************************************library(tidyverse)── Attaching packages ────────────────────────────────── tidyverse 1.3.0 ──✓ ggplot2 3.2.1 ✓ purrr 0.3.4
✓ tibble 2.1.3 ✓ dplyr 0.8.3
✓ tidyr 1.1.0 ✓ stringr 1.4.0
✓ readr 1.3.1 ✓ forcats 0.4.0── Conflicts ───────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()library(ggpubr)
Attaching package: 'ggpubr'The following object is masked from 'package:cowplot':
get_legendmkdir ../output/FigureDFFigure1
1A- location pic charts
fig1A_data=read.table("../output/FigureDF/nPAS_figure1.txt", header = T, stringsAsFactors = F)
fig1A_data$species <- factor(fig1A_data$species, labels = c("Chimpanzee~PAS", "Human~PAS"))
fig1A=ggplot(fig1A_data,aes(x="",y=prop, fill=loc)) + geom_bar(stat="identity",width=1, color="white")+ coord_polar("y", start=0) +theme_void() + facet_wrap(~species,labeller = label_parsed,strip.position = "left") + scale_fill_brewer(palette = "RdYlBu", name="Genic Location", labels=c("Coding", "5KB downstream", "Intronic","3' UTR", "5' UTR")) + theme(legend.position = "bottom",strip.text = element_text(size = 10, face = "italic",angle=270), text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold"),plot.margin = unit(c(0,0,0,0), "cm")) +labs(title="PAS genic locations are conserved between species", x="", y="")
fig1A
fig1B_data=read.table("../output/FigureDF/SeqConservation.txt",header = T,stringsAsFactors = F)
fig1B=ggplot(fig1B_data, aes(x=Set, by=Set, fill=region, y=PhyloP)) + geom_boxplot(notch = T) + scale_fill_brewer(palette = "RdYlBu") + scale_x_discrete(labels=c("-600", "-400", "-200", '0','200','400','600')) + labs(x="base pairs", title="PAS are more conserved \nthan surrounding regions") + guides(fill = FALSE) + theme_classic()+ theme(plot.title = element_text(hjust = 0.5, face="bold"), axis.text.x = element_text(size=10),axis.text.y = element_text(size=10),text=element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig1B
Figure 1C:
fig1c_data=read.table("../output/FigureDF/SignalSizeFigure.txt", header = T, stringsAsFactors = F)
fic1c=ggplot(fig1c_data, aes(y=propSS,by=Species,fill=Species,x=reorder(SS, -propSS))) + geom_bar(stat="identity", position = "dodge") + theme_classic() +theme(axis.text.x = element_text(size=10,angle = 90),plot.title = element_text(hjust = 0.5, face="bold"),axis.text.y = element_text(size=10),text=element_text(size=10), legend.position = "top",plot.margin = unit(c(0,0,0,0), "cm")) + scale_fill_brewer(palette = "Dark2", label=c("Chimp", "Human")) + labs(y="Proportion of PAS",title="Proportion of PAS with a signal site", x="")figure 1 :
row2=plot_grid(fig1B,fic1c, labels=c("b","c"), scale = c(.9,.9), nrow = 1)
fig1all=plot_grid(fig1A,row2, labels = c("a", ""),nrow = 2,rel_heights=c(.75,1 ),hjust=-12)
fig1all
pdf("../output/fig1.pdf", height=6, width=8)
fig1all
dev.off()png
2 Figure 2:
Pie charts for differences
PASlevel= read.table("../output/FigureDF/PASlevelDiff.txt", stringsAsFactors = F, header=T,col.names =c("sig", "n","gene","prop")) %>% mutate(set="PAS", test=c("Conserved", "Not Tested", "Divergent"))
genelevel= read.table("../output/FigureDF/GenelevelDiff.txt", stringsAsFactors = F, header = T, col.names =c("sig", "n","gene","prop")) %>% mutate(set="gene", test=c("Conserved", "Not Tested", "Divergent"))
isoformlevel= read.table("../output/FigureDF/IsoformlevelDiff.txt", stringsAsFactors = F, header = T, col.names =c("sig", "n","gene","prop")) %>% mutate(set="isoform",test=c("Conserved", "Not Tested", "Divergent"))
fig2a=PASlevel %>% bind_rows(genelevel) %>% bind_rows(isoformlevel)
fig2a$set=factor(fig2a$set, levels=c("PAS", "gene", "isoform"),labels = c("PAS~Differences", "Genes~with~PAS~Differneces", "Differences~isoform~diversity"))
fig2a$test=factor(fig2a$test,levels= c("Conserved", "Divergent","Not Tested"))
useCOl <- c("#d73027", "#4575b4","#fee090")
fig2aplot=ggplot(fig2a,aes(by=test, y=prop, x="", fill=test)) + geom_bar(stat="identity",width=1, color="white")+ coord_polar("y", start=0) +theme_void() + scale_fill_manual(values=useCOl,name="") + facet_wrap(~set,labeller = label_parsed,strip.position = "left") + theme(legend.position = "bottom",strip.text = element_text(size = 10, angle=270), text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12)) + labs(title="APA is functionally conserved at PAS and isoform diversity levels")Dominance plots
fig2cd_data=read.table("../output/FigureDF/DominantPAS.txt", header = T, stringsAsFactors = F)
fig2cd_data$cut=as.factor(fig2cd_data$cut)
fig2d=ggplot(fig2cd_data,aes(x=cut,y=PropSame,fill=cut)) + geom_bar(stat="identity") +geom_text(aes(label=nDom), position=position_dodge(width=0.9), vjust=1,size=3)+ scale_fill_brewer(palette = "RdYlBu")+theme_classic()+theme(legend.position = "none",text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm")) + labs(title="Most genes with a dominant PAS\n share the same dominant PAS", y="Proportion of Genes in Set", x="Dominance Cutoff")
fig2d
fig2c=ggplot(fig2cd_data,aes(x=cut,y=PropDom,fill=cut)) + geom_bar(stat="identity") +geom_text(aes(label=nDom), position=position_dodge(width=0.9), vjust=1, size=3) + scale_fill_brewer(palette = "RdYlBu")+theme_classic()+theme(legend.position = "none",text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm")) + labs(title="Proportion of tested Genes \nwith a dominant PAS", y="Proportion of Tested Genes", x="Dominance Cutoff")
fig2c
fig2row2=plot_grid(fig2c,fig2d, labels=c("b","c"), scale = c(.9,.9), nrow = 1)
fig2=plot_grid(fig2aplot,fig2row2, nrow = 2,labels = c("a",""),rel_heights=c(.8,1 ),hjust=-5)
fig2
pdf("../output/fig2.pdf", height=6, width=8)
fig2
dev.off()png
2 figure 3
fig3_data=read.table("../output/DEandAPA.txt", header = T, stringsAsFactors = F)
fig3_data2=read.table("../output/DEandAPA_sig.txt", header = T, stringsAsFactors = F)fig3a=ggplot(fig3_data,aes(y=deltaPAU, x=CorrectedlogFC)) + geom_point(alpha=.3) + geom_smooth(method="lm") + labs(title="APA v DE", x="DE log2 effect size", y="Difference in PAS Usage") + scale_color_brewer(palette = "Set1",name="", labels=c("Intronic", "3' UTR"))+ stat_cor(label.x = -8,label.y = -1) +theme_classic() + theme(text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig3a
fig3b=ggplot(fig3_data,aes(y=deltaPAU, x=CorrectedlogFC, col=loc)) + geom_point(alpha=.3) + geom_smooth(aes(col=loc),method="lm") + labs(title="APA v DE", x="DE log2 effect size", y="Difference in PAS Usage") + scale_color_brewer(palette = "Set1",name="", labels=c("Intronic", "3' UTR"))+ stat_cor(aes(col=loc),label.x = -8,label.y = c(-1,1)) +theme_classic() + theme(legend.position = "right",text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig3b
fig3c=ggplot(fig3_data2,aes(y=deltaPAU, x=CorrectedlogFC)) + geom_point(alpha=.3) + geom_smooth(method="lm") + labs(title="Significant differences in \nAPA and DE", x="DE log2 effect size", y="Difference in PAS Usage") + scale_color_brewer(palette = "Set1",name="", labels=c("Intronic", "3' UTR"))+ stat_cor(label.x = -8,label.y = -1)+theme_classic()+ theme(legend.position = "top",text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig3c
fig3d=ggplot(fig3_data2,aes(y=deltaPAU, x=CorrectedlogFC, col=loc)) + geom_point(alpha=.3) + geom_smooth(aes(col=loc),method="lm") + labs(title="Significant differences in\n APA and DE", x="DE log2 effect size", y="Difference in PAS Usage") + scale_color_brewer(palette = "Set1",name="", labels=c("Intronic", "3' UTR"))+ stat_cor(aes(col=loc),label.x = -8,label.y = c(-1,1))+theme_classic()+ theme(legend.position = "right",text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm") )
fig3d
fig3=plot_grid(fig3a, fig3b,fig3c,fig3d, scale = c(.9,.9,.9,.9), labels=c("a","b","c","d"),rel_widths=c(1,1.3,1,1.3))
fig3
pdf("../output/fig3.pdf", height=8, width=8)
fig3
dev.off()png
2 Spearman correlations for these:
cor(fig3_data$CorrectedlogFC, fig3_data$deltaPAU, method = "spearman")[1] -0.05303933fig3_data_utr=fig3_data %>% filter(loc=="utr3")
cor(fig3_data_utr$CorrectedlogFC, fig3_data_utr$deltaPAU, method = "spearman")[1] -0.05359158fig3_data_intron=fig3_data %>% filter(loc=="intron")
cor(fig3_data_intron$CorrectedlogFC, fig3_data_intron$deltaPAU, method = "spearman")[1] 0.04627481cor(fig3_data2$CorrectedlogFC, fig3_data2$deltaPAU, method = "spearman")[1] -0.1603421fig3_data2_utr=fig3_data2 %>% filter(loc=="utr3")
cor(fig3_data2_utr$CorrectedlogFC, fig3_data2_utr$deltaPAU, method = "spearman")[1] -0.2225137fig3_data2_intron=fig3_data2 %>% filter(loc=="intron")
cor(fig3_data2_intron$CorrectedlogFC, fig3_data2_intron$deltaPAU, method = "spearman")[1] 0.2201923figure 5
fig4Data=read.table("../output/FigureDF/DEandTEenrich.txt", header = T, stringsAsFactors = F)
fig4Data$Pval=as.numeric(fig4Data$Pval)
fig4Data$Enrichment=as.numeric(fig4Data$Enrichment)
fig4Data$Pheno=factor(fig4Data$Pheno, levels=c("Expression", "Translation", "Protein"))figure4a=ggplot(fig4Data,aes(x=sets,col=sets,y=Enrichment,label = round(Enrichment,3)))+ geom_bar(stat="identity",color="grey",aes(y=fig4Data$Enrichment),width=.01)+geom_point(size=10) + coord_flip() + geom_hline(yintercept = 1) + facet_grid(~Pheno)+scale_color_manual(values=useCOl) + labs( title="Genes with differences in APA are enriched\n in differentially expressed and differentially translated genes",x="", y="Enrichment")+geom_text(color = "black", size = 3) +scale_x_discrete(labels=c(Both="Both", OnlyAPA="PAS",OnlyIC= "ID"))+ theme_classic()+theme(legend.position = "none", text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
figure4a
figure4b=ggplot(fig4Data,aes(x=sets, y=-log10(Pval),fill=sets)) +geom_bar(stat = "identity",position = "dodge") +geom_hline(yintercept =1.3)+ labs(x="")+scale_x_discrete(labels=c(Both="Both", OnlyAPA="PAS",OnlyIC= "ID"))+ scale_fill_manual(values=useCOl,labels=c("Both", "PAS Level", "Isoform Diversity"), name="")+facet_wrap(~Pheno)+ theme_classic()+ theme(legend.position = "none",text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
figure4b
row2fig4=plot_grid(NULL, figure4b,NULL, rel_widths=c(0.12,1,.1), nrow = 1 )
fig4=plot_grid(figure4a,row2fig4,nrow =2, scale = c(.9,.9),labels = c("a","b"))
fig4
pdf("../output/fig5.pdf", height=6, width=8,useKerning=F)
fig4
dev.off()png
2 figure 5
fig5data=read.table("../output/FigureDF/SameDiffDomEnrichinDE.txt",header = T, stringsAsFactors = F)
fig5data$set=as.factor(fig5data$set)
fig5a=ggplot(fig5data,aes(x=set,group=type,col=set,y=Enrich))+ geom_bar(stat="identity",col="grey",alpha=.3,width=.01)+geom_point(size=10) + coord_flip()+ geom_hline(yintercept = 1) +scale_color_brewer(palette="RdYlBu")+geom_text(col="black",aes(label = round(Enrich,2)))+ facet_grid(~type)+labs(x="Dominance Cutoff", y="Enrichment",title="Enrichment for differentially expressed genes in genes\n with the same and different dominant PAS") + theme_classic()+ theme(legend.position = "none", text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=12),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig5a
fig5b=ggplot(fig5data,aes(x=set, y=-log10(Pval),fill=set)) + geom_bar(stat="identity") +labs(title="",x="Dominance Cutoff")+ scale_fill_brewer(palette = "RdYlBu") + theme(legend.position = "none")+ geom_hline(yintercept = 1.30103) + facet_grid(~type)+ theme_classic()+ theme(legend.position = "none", text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig5b
fig5=plot_grid(fig5a,fig5b,nrow = 2,scale = c(.9,.9),labels = c("a","b"), rel_heights = c(1,.8))
fig5
pdf("../output/fig4.pdf", height=7, width=7,useKerning=F)
fig5
dev.off()png
2 fig 6
fig6topdata=read.table("../output/FigureDF/DPnotDE.txt",header = T, stringsAsFactors = F)
fig6middata=read.table("../output/FigureDF/DPnotDE_trans.txt",header = T, stringsAsFactors = F)
fig6dapa=read.table("../output/FigureDF/PinteractiondAPA.txt",header = T, stringsAsFactors = F)
fig6both=read.table("../output/FigureDF/Pinteractionboth.txt",header = T, stringsAsFactors = F)
fib6ic=read.table("../output/FigureDF/PinteractiondIC.txt",header = T, stringsAsFactors = F)fig6a=ggplot(fig6topdata,aes(x=Set, fill=Set, y=Number))+ geom_bar(stat="identity")+ scale_fill_manual(values=useCOl)+geom_text(aes(label=Number), position=position_dodge(width=0.9), vjust=2)+ labs(title="Number of genes differentially expressed\n in protein but not mRNA", y="Number of Genes",x="")+scale_x_discrete(labels=c(Both="Both", OnlyAPA="PAS",OnlydIC= "ID"))+ theme_classic()+theme(legend.position = "none", text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig6a
fig6b=ggplot(fig6topdata,aes(x=Set, fill=Set, y=Prop))+ geom_bar(stat="identity")+ scale_fill_manual(values=useCOl) + labs(title="Proportions of genes differentially expressed\n in protein but not mRNA", y="Proportion of Genes",x="")+geom_text(aes(label=round(Prop,3)), position=position_dodge(width=0.9), vjust=2) +scale_x_discrete(labels=c(Both="Both", OnlyAPA="PAS",OnlydIC= "ID"))+ theme_classic()+theme(legend.position = "none", text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig6b
fig6c= ggplot(fig6middata, aes(x=set,by=dTE, y=ndTE,fill=set, alpha=dTE)) +geom_bar(stat="identity", position = "dodge") + labs(title="", y="Number of Genes",x="") + scale_fill_manual(values = useCOl ) + scale_alpha_manual(values=c(.6, 1),name="Differentially translated") + geom_text(aes(label=ndTE), position=position_dodge(width=0.9), vjust=1)+guides(fill = FALSE)+scale_x_discrete(labels=c(Both="Both", OnlyAPA="PAS",OnlyIC= "ID"))+theme_classic()+ theme(legend.position = "top", legend.justification = "center", text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig6c
fig6d=ggplot(fig6middata, aes(x=set,by=dTE, y=ndTE,fill=set, alpha=dTE)) +geom_bar(stat="identity", position = "fill") + labs(title="", y="Proportion of Genes",x="") + scale_fill_manual(values = useCOl ) + scale_alpha_manual(values=c(.6, 1),name="Differentially translated") + guides(fill = FALSE)+scale_x_discrete(labels=c(Both="Both", OnlyAPA="PAS",OnlyIC= "ID"))+ theme(legend.position = "top",legend.justification = "center", text=element_text(size=10),plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),axis.text.x = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
fig6d
#fig6e=ggplot(fig6both,aes(x=dPnotDE, y=log10(NormInter),fill=dPnotDE)) + geom_boxplot(notch = T) + stat_compare_means( label.x = 1.25, label.y = 1.5) + scale_fill_manual(values = c("grey", "#d73027"))+ labs(x="Differentally expressed in protein \n not in mRNA", y="log10(Interaction)", title="") + theme_classic() + theme(axis.text.x=element_text(angle=90, hjust=0, size = 10), text= element_text(size=10), legend.position = "none",plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
#fig6e
#fig6f=ggplot(fig6dapa,aes(x=dPnotDE, y=log10(NormInter),fill=dPnotDE)) + geom_boxplot(notch = T) + stat_compare_means( label.x = 1.25, label.y = 1.5) + scale_fill_manual(values = c("grey", "#4575b4")) + labs(x="Differentally expressed in protein \n not in mRNA", y="log10(Interaction)", title="") + theme_classic() + theme(axis.text.x=element_text(angle=90, hjust=0, size = 10), text= element_text(size=10), legend.position = "none",plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
#fig6f
#fig6g=ggplot(fib6ic,aes(x=dPnotDE, y=log10(NormInter),fill=dPnotDE)) + geom_boxplot(notch = T) + stat_compare_means( label.x = 1.25, label.y = 1.5) + scale_fill_manual(values = c("grey", "#fee090")) + labs(x="Differentally expressed in protein \n not in mRNA", y="log10(Interaction)", title="") + theme_classic() + theme(axis.text.x=element_text(angle=90, hjust=0, size = 10), text= element_text(size=10), legend.position = "none",plot.title = element_text(hjust = 0.5, face="bold",size=10),axis.text.y = element_text(size=10),plot.margin = unit(c(0,0,0,0), "cm"))
#fig6gfig6top=plot_grid(fig6a,fig6b, labels = c("a","b"), scale = c(.9,.9),nrow = 1)
fig6mid=plot_grid(fig6c,fig6d, labels = c("c","d"), scale = c(.9,.9),nrow = 1)
#fig6botom=plot_grid(fig6e,fig6f, fig6g, labels = c("e","f","g"), scale = c(.9,.9,.9),nrow = 1)
fig6=plot_grid(fig6top,fig6mid,nrow = 2, rel_heights = c(1,1))
fig6
pdf("../output/fig6.pdf", height=8, width=8,useKerning=F)
fig6
dev.off()png
2 Draft July 25 switch figure 4 and 5
sessionInfo()R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggpubr_0.3.0 forcats_0.4.0 stringr_1.4.0 dplyr_0.8.3
[5] purrr_0.3.4 readr_1.3.1 tidyr_1.1.0 tibble_2.1.3
[9] ggplot2_3.2.1 tidyverse_1.3.0 cowplot_1.0.0
loaded via a namespace (and not attached):
[1] httr_1.4.1 jsonlite_1.6 carData_3.0-2
[4] modelr_0.1.8 assertthat_0.2.1 cellranger_1.1.0
[7] yaml_2.2.0 pillar_1.4.2 backports_1.1.4
[10] lattice_0.20-38 glue_1.3.1 digest_0.6.20
[13] RColorBrewer_1.1-2 promises_1.0.1 ggsignif_0.5.0
[16] rvest_0.3.5 colorspace_1.4-1 plyr_1.8.4
[19] htmltools_0.3.6 httpuv_1.5.1 pkgconfig_2.0.2
[22] broom_0.5.2 haven_2.3.1 scales_1.1.0
[25] whisker_0.3-2 openxlsx_4.1.0.1 later_0.8.0
[28] rio_0.5.16 git2r_0.26.1 generics_0.0.2
[31] farver_2.0.1 car_3.0-5 withr_2.1.2
[34] lazyeval_0.2.2 cli_2.2.0 magrittr_1.5
[37] crayon_1.3.4 readxl_1.3.1 evaluate_0.14
[40] fs_1.3.1 fansi_0.4.0 nlme_3.1-140
[43] rstatix_0.5.0 xml2_1.3.2 foreign_0.8-71
[46] tools_3.6.1 data.table_1.13.2 hms_0.5.3
[49] lifecycle_0.1.0 munsell_0.5.0 reprex_0.3.0
[52] zip_2.0.3 compiler_3.6.1 rlang_0.4.6
[55] grid_3.6.1 rstudioapi_0.10 labeling_0.3
[58] rmarkdown_1.13 gtable_0.3.0 abind_1.4-5
[61] DBI_1.1.0 curl_3.3 reshape2_1.4.3
[64] R6_2.4.0 lubridate_1.7.4 knitr_1.23
[67] workflowr_1.6.2 rprojroot_1.3-2 stringi_1.4.3
[70] Rcpp_1.0.5 vctrs_0.3.0 dbplyr_1.4.2
[73] tidyselect_1.1.0 xfun_0.8