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hamlets_ILD_vision_pigmentation
hamlets_ILD_vision_pigmentation
Commit 7df22ce7 authored by Kosmas Hench's avatar Kosmas Hench
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- F1 from R script to Rmd
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0_data/0_img/legend-map.svg
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......@@ -16,7 +16,7 @@
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......@@ -41,13 +41,13 @@
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0_data/0_resources/outlier_regions.bed 0 → 100644
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LG04 5835001 5925000 1
LG04 6555001 6645000 2
LG08 1945001 2090000 3
LG08 9505001 9595000 4
LG08 10270001 10420000 5
LG08 12810001 12895000 6
LG08 12945001 13010000 7
LG08 14825001 14875000 8
LG09 17820001 17930000 9
LG09 20995001 21085000 10
LG12 15050001 15105000 11
LG12 20085001 20355000 12
LG12 22150001 22290000 13
LG17 21340001 21415000 14
LG17 22505001 22660000 15
LG20 13840001 13900000 16
LG23 13965001 14030000 17
LG23 15445001 15530000 18
0_data/0_scripts/F4.functions.R
View file @ 7df22ce7
......@@ -134,11 +134,13 @@ trplot <- function(sel){
scale_x_continuous(expand=c(0,0))+
scale_y_continuous(expand=c(0,0),
trans = 'reverse')+
scale_fill_gradientn(name=expression(bar(r^2)),colours=clr,
values=rescale(c(1,.08,.03,.015,.01,0)),
limits=c(0,1),guide = 'legend',breaks=c(0,.005,.01,.02,.03,.1,1))+
scale_fill_gradientn(name=expression(bar(italic(r)^2)),colours=clr,
values=rescale(c(1,.5,.08,.03,.015,.01,0)),
limits=c(0,1),
guide = 'legend',breaks=c(0,.005,.01,.02,.03,.1,1))+
theme_void()+
theme(legend.position = c(.7,.75),legend.direction = 'vertical')
theme(legend.position = c(.9,.75),
legend.direction = 'vertical')
} else {
p1 <- ggplot(dt %>% filter(!is.na(Mval)),aes(fill=Mval))+
coord_equal()+
......
0_data/0_scripts/F4.genomeWide_box.R
View file @ 7df22ce7
......@@ -34,7 +34,7 @@ pBOX <- ggplot(BW,aes(x=run,y=R.2))+
geom_point(inherit.aes = F, data=dt2,aes(x=run,y=val,fill=type),shape=23,size=1)+
scale_x_discrete(labels = expression(Global,Panama,Belize,Honduas,
italic("H. nigricans"),italic("H. puella"),italic("H. unicolor")))+
scale_y_continuous('genome wide ILD (r²)')+
scale_y_continuous(name=expression(genome~wide~ILD~(italic(r)^2)))+
scale_fill_manual('',values = clr[c(6,1)],labels=c('mean','median'))+
guides(shape = guide_legend(ncol = 1))+
theme(legend.position = c(-.4,1.27),
......
0_data/0_scripts/F4.peakArea_box.R
View file @ 7df22ce7
......@@ -31,7 +31,7 @@ boxGenes <- ggplot(dataBoxGenes,aes(x=xS))+
geom_boxplot(aes(y=R.2),fill=BC,width=.7,outlier.size = .1) +
geom_point(data=BoxGenes_summary,aes(y=val,fill=type),shape=23,size=1)+
coord_fixed(ylim=c(0,.031),ratio = 250)+
scale_y_continuous('ILD around \ncandidate genes (r²)')+
scale_y_continuous(expression(candidate~gene~ILD~(italic(r)^2)))+
scale_x_discrete(labels = expression(Global,Panama,Belize,Honduas,
italic("H. nigricans"),italic("H. puella"),italic("H. unicolor")))+
scale_fill_manual('',values = clr[c(6,1)],labels=c('mean','median'))+
......@@ -39,6 +39,7 @@ boxGenes <- ggplot(dataBoxGenes,aes(x=xS))+
theme(legend.position = c(.35,1.27),
text = element_text(size=10),
axis.title.x = element_blank(),
axis.title.y = element_text(hjust=1.25),
axis.text.y = element_text(size=7),
axis.text.x = element_text(size=7,angle=45,hjust = 1),
panel.background = element_blank(),
......
0_data/0_scripts/S07.functions.R
View file @ 7df22ce7
......@@ -188,7 +188,7 @@ trplot <- function(sel){
scale_x_continuous(expand=c(0,0))+
scale_y_continuous(expand=c(0,0),
trans = 'reverse')+
scale_fill_gradientn(name=expression(bar(r^2)),colours=clr,
scale_fill_gradientn(name=expression(bar(italic(r)^2)),colours=clr,
values=rescale(c(1,.08,.03,.015,.01,0)),
limits=c(0,1),guide = 'legend',breaks=c(0,.005,.01,.02,.03,.1,1))+
scale_color_manual(values=viridis_pal(option='A')(6))+theme_void()+
......
0_data/0_scripts/S14.functions.R 0 → 100644
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get_anno_df_single_line <- function(searchLG,gfffile,
xrange,
anno_rown=4){
gff_filter <- list(seqid=searchLG)
data <- as.data.frame(readGFF(gfffile,filter=gff_filter)) %>% mutate(Parent=as.character(Parent))#%>%
#rowwise() %>% mutate(Parent=ifelse(length(Parent)==0,ID,Parent))
mRNAs <- data %>% filter(type=='mRNA',end>xrange[1],start<xrange[2]) %>%
ungroup() %>% mutate(yl=row_number()%%anno_rown+2) %>% rowwise()%>%
mutate(checkStart =ifelse(start<xrange[1],-Inf,start),
checkEnd =ifelse(end>xrange[2],Inf,end),
ps=ifelse(strand=='-',checkEnd,checkStart),
pe=ifelse(strand=='-',checkStart,checkEnd),
labelx=mean(c(sort(c(xrange[1],ps))[2],
sort(c(xrange[2],pe))[1])),
window='bold(Gene)') %>%
select(-Parent);
names(mRNAs)[names(mRNAs)=='ID'] <- 'Parent'
exons <- data %>% filter(type=='exon',end>xrange[1],start<xrange[2]) %>%
merge(.,mRNAs %>% select(Parent,yl),by='Parent',all.x=T) %>%
mutate(ps=ifelse(strand=='-',end,start),
pe=ifelse(strand=='-',start,end),
window='bold(Gene)')
return(list(mRNAs,exons))}
0_data/0_scripts/S14.plot_fun.R 0 → 100644
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create_K_plot <- function(searchLG,gfffile,xr,xr2,muskID){
source('../../0_data/0_scripts/S14.functions.R');
source('../../0_data/0_scripts/F3.getFSTs.R')
highclr <- '#3bb33b'
theme_set(theme_minimal(base_size = 6))
if(xr[1]>xr[2]){print('error: ill conditioned x-range')}
wdth <- .3
# get gene models
df_list <- get_anno_df_single_line(searchLG=searchLG,gfffile=gfffile,xrange=xr,anno_rown=4)
# get fst values
fst_list <- getFSTS(searchLG,xr,c(),highclr)
# data_fst_pw<-fst_list$data_fst_pw;
global_fst<-fst_list$global_fst;
data_fst<-fst_list$data_fst
clr <- c('#fb8620','#1b519c','#d93327')
annoclr <- c('lightgray',highclr,rgb(.3,.3,.3))[1:3]
df_list[[1]] <- df_list[[1]] %>%
rowwise() %>%
mutate(label=unlist(strsplit(tolower(Parentgenename), "_"))[1])
LW <- .3;lS <- 9;tS <- 6
plotSET <- theme(rect = element_blank(),
text=element_text(size=tS,color='black'),
panel.grid.major = element_line(colour = rgb(.92,.92,.92)),
panel.grid.minor = element_line(colour = rgb(.95,.95,.95)),
plot.background = element_blank(),
plot.margin = unit(c(3,7,3,3),'pt'),
panel.background = element_blank(),#element_rect(colour = 'gray',fill=NULL),
legend.position = 'none',#c(.8,.3),
legend.direction = 'horizontal',
axis.title.y = element_blank(),
axis.title.x = element_blank(),#element_text(size=13,face='bold',color='black'),
strip.text.y = element_text(size=lS,color='black'),
axis.text.x = element_blank(),#element_text(size=11,color='black'),
strip.placement = "outside",
panel.border = element_blank()
)
Gclr=rgb(.3,.3,.3)
range_df <- data.frame(x=xr2[1],x2=xr2[2])
range_clr <- rgb(0,0,.4,.1)
p11 <- ggplot()+coord_cartesian(xlim=xr/1000)+
geom_rect(data=range_df,aes(xmin = x/1000,xmax=x2/1000,ymin=-Inf,ymax=Inf),
col=range_clr,fill=range_clr)+
geom_rect(data=df_list[[2]],
aes(xmin=ps/1000,xmax=pe/1000,ymin=yl-(wdth/2),ymax=yl+(wdth/2),group=Parent),
col=Gclr,fill=Gclr,lwd=.1)+
geom_segment(data=(df_list[[1]]%>%filter(strand%in%c('+','-'))),
aes(x=ps/1000,xend=pe/1000,y=yl,yend=yl,group=Parent),lwd=.1,
arrow=arrow(length=unit(2,"pt"),type='closed'),color='black')+
geom_segment(data=(df_list[[1]]%>%filter(!strand%in%c('+','-'))),
aes(x=ps/1000,xend=pe/1000,y=yl,yend=yl,group=Parent),lwd=.2,color='black')+
geom_text(data=df_list[[1]],
aes(x=labelx/1000,label=gsub('000000','...',label),y=yl-.5),size=1.8)+
facet_grid(window~.,scales='free_y',
switch = 'y',labeller = label_parsed,as.table = T)+
# color settings
#scale_color_manual(values=annoclr,breaks=c("x","y","z"),guide=F)+
#scale_fill_manual(values=annoclr,guide=F)+
scale_x_continuous(name=paste0(searchLG,' (',muskID,', kb)'),expand=c(0,0),position = 'top')+
scale_y_continuous(breaks = seq(0,.75,length.out = 4))+
theme(rect = element_blank(),
text=element_text(size=tS,color='black'),
panel.grid.major = element_blank(),#element_line(colour = rgb(.92,.92,.92)),
panel.grid.minor = element_blank(),#element_line(colour = rgb(.95,.95,.95)),
plot.background = element_blank(),
panel.background = element_blank(),#element_rect(colour = 'gray',fill=NULL),
# plot.margin = unit(c(3,3,3,3),'pt'),
legend.position = c(.8,.3),
legend.direction = 'horizontal',
axis.title.y = element_blank(),
axis.title.x = element_text(size=lS,face='bold',color='black'),
strip.text.y = element_text(size=lS,color='black'),
axis.text.x = element_text(size=tS,color='black'),
strip.placement = "outside",
panel.border = element_blank()
);
p12 <- ggplot()+coord_cartesian(xlim=xr)+
geom_rect(data=range_df,aes(xmin = x,xmax=x2,ymin=-Inf,ymax=Inf),
col=range_clr,fill=range_clr)+
geom_point(data=global_fst,aes(x=POS,y=WEIR_AND_COCKERHAM_FST),col=global_fst$clr,size=.2)+
geom_point(data=global_fst,aes(x=POS,y=WEIR_AND_COCKERHAM_FST),col=global_fst$clr2,size=.3)+
# add pairwise fsts as lines (10 kb / 1kb)
geom_line(data=(data_fst %>% filter(POS > xr[1],POS<xr[2]))
,aes(x=POS,y=WEIGHTED_FST,col=run),lwd=LW)+
# geom_line(data=(data_fst_pw %>% filter(POS > xr[1],POS<xr[2]))
# ,aes(x=POS,y=WEIGHTED_FST,col=run,linetype=group),lwd=1)+
scale_color_manual(values=c(clr,annoclr),breaks=c("nig-pue","nig-uni","pue-uni"),guide=F)+
scale_fill_manual(values=annoclr,guide=F)+
facet_grid(window~.,scales='free_y',
switch = 'y',labeller = label_parsed,as.table = T)+
scale_x_continuous(name=searchLG,expand=c(0,0),position = 'top')+
scale_y_continuous(breaks = seq(0,.75,length.out = 4))+
scale_linetype(name='location',label=c('Belize','Honduras','Panama'))+
guides(linetype= guide_legend(override.aes = list(color = 'black')))+plotSET
p2 <- plot_grid(p11,p12,
ncol = 1,align = 'v',axis = 'r',rel_heights = c(1.3,1))
return(p2)}
\ No newline at end of file
0_data/0_scripts/run_parallelNewHybrids.R
View file @ 7df22ce7
......@@ -11,4 +11,4 @@ path.hold <- getwd()
your.NH <- paste0(args[3],"/newhybrids/")
parallelnh_OSX(folder.data = paste0(path.hold,"/",args[1],"/"),
where.NH = your.NH, burnin = 1000000, sweeps = 3000000)
\ No newline at end of file
where.NH = your.NH, burnin = 1000000, sweeps = 10000000)
\ No newline at end of file
2_reSeq-scripts/2-2_popGen/2.2.10.2.vcf2newHybrids.sh
View file @ 7df22ce7
......@@ -24,7 +24,7 @@ vcftools \
--thin 3000 \
--out $WORK/2_output/08_popGen/11_newHyb/NHrecode/newHyb.$k \
--positions $WORK/2_output/08_popGen/11_newHyb/snpSets/filterSet.1k.$k.snps \
--recode \
--recode
$WORK/0_data/0_scripts/subsetVcf newHyb.$k.recode.vcf 120
......
3_figures/0_data/0_img/legend-adaptation-cairo.svg deleted 100644 → 0
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3_figures/0_data/0_img/legend-pw-cairo.svg deleted 100644 → 0
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This source diff could not be displayed because it is too large. You can view the blob instead.
3_figures/3_figures.Rproj deleted 100644 → 0
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Version: 1.0
RestoreWorkspace: Default
SaveWorkspace: Default
AlwaysSaveHistory: Default
EnableCodeIndexing: Yes
UseSpacesForTab: Yes
NumSpacesForTab: 2
Encoding: UTF-8
RnwWeave: Sweave
LaTeX: pdfLaTeX
3_figures/F2.Rmd
View file @ 7df22ce7
......@@ -264,8 +264,8 @@ F2 <- ggdraw(p1)+
The *F~ST~* outlier windows are then exported to be used as reference in other figures.
```{r exportMusks, eval=FALSE}
write.table(x = data2, file = 'fst_outlier_windows.txt',sep='\t',quote = F,row.names = F)
write.table(x = musks, file = 'fst_outlier_ID.txt',sep='\t',quote = F,row.names = F)
write.table(x = data2, file = '../../0_data/0_resources/fst_outlier_windows.txt',sep='\t',quote = F,row.names = F)
write.table(x = musks, file = '../../0_data/0_resources/fst_outlier_ID.txt',sep='\t',quote = F,row.names = F)
```
......
3_figures/F4.Rmd
View file @ 7df22ce7
......@@ -369,7 +369,7 @@ Then, the base plot is created and stored in `p1`.
scale_y_continuous(expand=c(0,0),
trans = 'reverse')+
# manual color gradient for LD data
scale_fill_gradientn(name=expression(bar(r^2)),colours=clr,
scale_fill_gradientn(name=expression(bar(italic(r)^2)),colours=clr,
values=rescale(c(1,.08,.03,.015,.01,0)),
limits=c(0,1),guide = 'legend',breaks=c(0,.005,.01,.02,.03,.1,1))+
# plot layout theme
......@@ -480,7 +480,7 @@ pBOX <- ggplot(BW,aes(x=run,y=R.2))+
# settting the axis and color labels
scale_x_discrete(labels = expression(Global,Panama,Belize,Honduas,
italic("H. nigricans"),italic("H. puella"),italic("H. unicolor")))+
scale_y_continuous('genome wide ILD (r²)')+
scale_y_continuous(name=expression(genome~wide~ILD~(italic(r)^2)))+
scale_fill_manual('',values = clr[c(6,1)],labels=c('mean','median'))+
# formatting the legend
guides(shape = guide_legend(ncol = 1))+
......@@ -555,7 +555,7 @@ boxGenes <- ggplot(dataBoxGenes,aes(x=xS))+
# set a fixed aspect ratio
coord_fixed(ylim=c(0,.031),ratio = 133)+
# settting the axis and color labels
scale_y_continuous('ILD around \ncandidate genes (r²)')+
scale_y_continuous(expression(candidate~gene~ILD~(italic(r)^2)))+
scale_x_discrete(labels = expression(Global,Panama,Belize,Honduas,
italic("H. nigricans"),italic("H. puella"),italic("H. unicolor")))+
scale_fill_manual('',values = clr[c(6,1)],labels=c('mean','median'))+
......@@ -565,6 +565,7 @@ boxGenes <- ggplot(dataBoxGenes,aes(x=xS))+
theme(legend.position = c(.35,1.27),
text = element_text(size=10),
axis.title.x = element_blank(),
axis.title.y = element_text(hjust=1.25),
axis.text.y = element_text(size=7),
axis.text.x = element_text(size=7,angle=45,hjust = 1),
panel.background = element_blank(),
......
3_figures/F5.Rmd
View file @ 7df22ce7
......@@ -87,7 +87,7 @@ Finally, the complete Figure 5 is put together.
```{r finalPlot,results='hide', message=FALSE, warning=FALSE}
F5 <- ggdraw(pGr8)+
draw_grob(pGr9,0,0,1,1)+
draw_grob(leg,-.65,.04,1,1)+
draw_grob(leg,-.85,.04,1,1)+
draw_grob(pGr10,0,0,1,1)+
draw_grob(npGrob, 0.7, 0.7, 0.28, 0.1)+
draw_grob(nuGrob, 0.7, 0.37, 0.28, 0.1)+
......@@ -98,7 +98,7 @@ The final figure is then exported using `ggsave()`.
```{r, eval=FALSE}
#ggsave(plot = F5,filename = '../output/F5.pdf',width = 91.5,height = 145,units = 'mm',device = cairo_pdf)
ggsave(plot = F5,filename = '../output/F5.png',width = 91.5,height = 145,units = 'mm',dpi = 150)
ggsave(plot = F5,filename = '../output/F5.png',width = 91.5,height = 155,units = 'mm',dpi = 150)
```
<center>
......
3_figures/F_scripts/F2.R
View file @ 7df22ce7
......@@ -130,8 +130,8 @@ p1 <- ggplot()+
)+
facet_grid(RUN~.)
write.table(x = data2, file = 'fst_outlier_windows.txt',sep='\t',quote = F,row.names = F)
write.table(x = musks, file = 'fst_outlier_ID.txt',sep='\t',quote = F,row.names = F)
write.table(x = data2, file = '../../0_data/0_resources/fst_outlier_windows.txt',sep='\t',quote = F,row.names = F)
write.table(x = musks, file = '../../0_data/0_resources/fst_outlier_ID.txt',sep='\t',quote = F,row.names = F)
legGrob <- gTree(children=gList(pictureGrob(readPicture("../../0_data/0_img/legend-pw-cairo.svg"))))
carGrob <- gTree(children=gList(pictureGrob(readPicture("../../0_data/0_img/caribbean-cairo.svg"))))
......
3_figures/F_scripts/F5.R
View file @ 7df22ce7
......@@ -32,10 +32,10 @@ leg <- get_legend(plts[[1]]+theme(legend.text = element_text(size = 5),
F5 <- ggdraw(pGr8)+
draw_grob(pGr9,0,0,1,1)+
draw_grob(leg,-.65,.04,1,1)+
draw_grob(leg,-.85,.04,1,1)+
draw_grob(pGr10,0,0,1,1)+
draw_grob(npGrob, 0.7, 0.7, 0.28, 0.1)+
draw_grob(nuGrob, 0.7, 0.37, 0.28, 0.1)+
draw_grob(puGrob, 0.7, .04, 0.28, 0.1)
ggsave(plot = F5,filename = '../output/F5.png',width = 91.5,height = 145,units = 'mm',dpi = 150)
\ No newline at end of file
ggsave(plot = F5,filename = '../output/F5.png',width = 91.5,height = 155,units = 'mm',dpi = 150)
\ No newline at end of file
3_figures/S01/S01.R → 3_figures/F_scripts/S01.R
View file @ 7df22ce7
......@@ -6,8 +6,8 @@ library(grConvert)
library(tidyverse)
library(cowplot)
convertPicture("circos.svg",'circos-cairo.svg')
cir <- gTree(children=gList(pictureGrob(readPicture("circos-cairo.svg"))))
convertPicture("../S01/circos.svg",'../S01/circos-cairo.svg')
cir <- gTree(children=gList(pictureGrob(readPicture("../S01/circos-cairo.svg"))))
GA <- gTree(children=gList(pictureGrob(readPicture("../../0_data/0_img/GA-cairo.svg"))))
HP <- gTree(children=gList(pictureGrob(readPicture("../../0_data/0_img/puella-cairo.svg"))))
......
3_figures/F_scripts/S02.R
View file @ 7df22ce7
......@@ -64,8 +64,8 @@ data$RUN <- factor(as.character(data$RUN),
levels=c('PN','NU','PU','PPNP','NPUP','PPUP','PBNB','NBUB','PBUB','PHNH','NHUH','PHUH'))
data$COL <- factor(as.character(data$COL),levels=c('PN','PU','NU'))
data2 <- read.csv('fst_outlier_windows.txt', sep='\t')
musks <- read.csv('fst_outlier_ID.txt', sep='\t')
data2 <- read.csv('../../0_data/0_resources/fst_outlier_windows.txt', sep='\t')
musks <- read.csv('../../0_data/0_resources/fst_outlier_ID.txt', sep='\t')
clr <- c('#fb8620','#d93327','#1b519c')
annoclr <- rgb(.4,.4,.4)
......
3_figures/F_scripts/S07.R
View file @ 7df22ce7
......@@ -49,7 +49,7 @@ sX <- -.03;
S07 <- ggdraw(pGr1)+
draw_plot(pGRAD,.307,-.018,.16,.53)+
draw_grob(pGr2,0,0,1,1)+
draw_grob(leg,.15,-.08,1,1)+
draw_grob(leg,.2,-.08,1,1)+
draw_grob(pGr3,0,0,1,1)+
draw_grob(pGr4,0,0,1,1)+
draw_grob(pGr5,0,0,1,1)+
......
3_figures/F_scripts/S09.R
View file @ 7df22ce7
......@@ -54,11 +54,11 @@ data$RUN <- factor(as.character(data$RUN),
levels=c('BH','BP','HP','BHN','BPN','HPN','BHP','BPP','HPP','BHU','BPU','HPU'))
data$COL <- factor(as.character(data$COL),levels=c('BH','BP','HP'))
data2 <- read.csv('fst_outlier_windows.txt', sep='\t') %>%
data2 <- read.csv('../../0_data/0_resources/fst_outlier_windows.txt', sep='\t') %>%
select(-RUN) %>%
group_by(musk) %>%
summarise_all(function(x){x[1]})
musks <- read.csv('fst_outlier_ID.txt', sep='\t') %>%
musks <- read.csv('../../0_data/0_resources/fst_outlier_ID.txt', sep='\t') %>%
select(-RUN) %>%
group_by(musk) %>%
summarise_all(function(x){x[1]}) %>%
......
3_figures/F_scripts/S10.R
View file @ 7df22ce7
......@@ -54,11 +54,11 @@ data$RUN <- factor(as.character(data$RUN),
levels=c('BH','BP','HP','BHN','BPN','HPN','BHP','BPP','HPP','BHU','BPU','HPU'))
data$COL <- factor(as.character(data$COL),levels=c('BH','BP','HP'))
data2 <- read.csv('fst_outlier_windows.txt', sep='\t') %>%
data2 <- read.csv('../../0_data/0_resources/fst_outlier_windows.txt', sep='\t') %>%
select(-RUN) %>%
group_by(musk) %>%
summarise_all(function(x){x[1]})
musks <- read.csv('fst_outlier_ID.txt', sep='\t') %>%
musks <- read.csv('../../0_data/0_resources/fst_outlier_ID.txt', sep='\t') %>%
select(-RUN) %>%
group_by(musk) %>%
summarise_all(function(x){x[1]}) %>%
......
3_figures/F_scripts/S12.R
View file @ 7df22ce7
......@@ -37,4 +37,4 @@ S12 <- ggdraw(pGr8)+
draw_grob(nuGrob, 0.7, 0.34, 0.28, 0.1)+
draw_grob(puGrob, 0.7, .01, 0.28, 0.1)
ggsave(plot = S12,filename = '../output/S12.png',width = 91.5,height = 155,units = 'mm',dpi = 150)
\ No newline at end of file
ggsave(plot = S12,filename = '../output/S12.png',width = 91.5,height = 160,units = 'mm',dpi = 150)
\ No newline at end of file
3_figures/F_scripts/S13.R
View file @ 7df22ce7
......@@ -64,7 +64,8 @@ p3 <- plotPCA(pca=panPCA, dataAll=(dataAll %>% filter(spec!='gum')), locIN='boc'
cp1 <- plot_grid(pbel+theme(legend.position = 'none'),p1,
phon+theme(legend.position = 'none'),p2,
pboc+theme(legend.position = 'none'),p3,
ncol = 2,rel_heights = c(1,1,1),rel_widths = c(0.65,0.35));
ncol = 2,rel_heights = c(1,1,1),
rel_widths = c(0.65,0.35),labels=c('a','b',rep('',4)),label_size = 10);
legGrob <- gTree(children=gList(pictureGrob(readPicture("../../0_data/0_img/legend_NH-cairo.svg"))))
belGrob <- gTree(children=gList(pictureGrob(readPicture("../../0_data/0_img/belize-cairo.svg"))))
......@@ -76,22 +77,23 @@ ysc <- .008
yd <- .3025
labX <- .675
bclr <- rgb(.9,.9,.9)
boxes = data.frame(x=rep(labX-.015,3),y=c(ys,ys+yd+ysc,ys+(yd+ysc)*2))
boxes = data.frame(x=rep(labX-.015,3),
y=c(ys,ys+yd+ysc,ys+(yd+ysc)*2))
S13 <- ggdraw()+
geom_rect(data = boxes, aes(xmin = x, xmax = x + .03, ymin = y, ymax = y + yd),
geom_rect(data = boxes, aes(xmin = x, xmax = x + .03, ymin = y+.07, ymax = y + yd+c(.07,.07,.05)),
colour = NA, fill = c(rep(bclr,3)))+
draw_label('Belize', x = labX, y = boxes$y[3]+.13,
draw_label('Belize', x = labX, y = boxes$y[3]+.20,
size = 13, angle=-90)+
draw_label('Honduras', x = labX, y = boxes$y[2]+.13,
draw_label('Honduras', x = labX, y = boxes$y[2]+.20,
size = 13, angle=-90)+
draw_label('Panama', x = labX, y = boxes$y[1]+.13,
draw_label('Panama', x = labX, y = boxes$y[1]+.20,
size = 13, angle=-90)+
draw_label('Posterior probability',x=.01,y=.5,size = 15, angle=90)+
draw_grob(legGrob,0,.93,1,.07)+
draw_plot(cp1,.0,0,1,.93)+
draw_grob(belGrob, labX-.0225, boxes$y[3]+.84*yd, .045, .045)+
draw_grob(honGrob, labX-.0225, boxes$y[2]+.84*yd, .045, .045)+
draw_grob(panGrob, labX-.0225, boxes$y[1]+.84*yd, .045, .045)
draw_label('Posterior probability',x=.01,y=.57,size = 15, angle=90)+
draw_grob(legGrob,0,0,1,.07)+
draw_plot(cp1,.0,.07,1,.93)+
draw_grob(belGrob, labX-.0225, boxes$y[3]+.84*yd+.05, .045, .045)+
draw_grob(honGrob, labX-.0225, boxes$y[2]+.84*yd+.07, .045, .045)+
draw_grob(panGrob, labX-.0225, boxes$y[1]+.84*yd+.07, .045, .045)
ggsave(plot = S13,filename = '../output/S13.pdf',width = 183,height = 235,units = 'mm',device = cairo_pdf)
3_figures/F_scripts/S14.R 0 → 100644
View file @ 7df22ce7
#!/usr/bin/env Rscript
library(grid)
library(gridSVG)
library(grImport2)
library(grConvert)
library(tidyverse)
library(rtracklayer)
library(hrbrthemes)
library(cowplot)
require(rtracklayer)
source('../../0_data/0_scripts/S14.plot_fun.R')
dat <- read.csv('../../0_data/0_resources/outlier_regions.bed',sep='\t',header = FALSE,stringsAsFactors = FALSE)
mar <- 10^5
mI <- c('-E','','-F',rep('',3),'-G','','-A',rep('',2),'-B','-C','','-D','-H',rep('',2))
plts <- list()
for(k in 1:18){
print(k)
x1 <- dat$V2[k]
x2 <- dat$V3[k]
plts[[k]] <- create_K_plot(searchLG = dat$V1[k],
gfffile = '../../1-output/09_gff_from_IKMB/HP.annotation.named.gff',
xr = c(x1-mar,x2+mar),
xr2=c(x1,x2),
muskID = paste0(k,mI[k]))
}
legGrob <- gTree(children=gList(pictureGrob(readPicture("../../0_data/0_img/legend-pw-cairo.svg"))))
p1 <- plot_grid(plts[[1]],plts[[2]],
plts[[3]], plts[[4]],
plts[[5]],plts[[6]],
labels=letters[1:6],label_size = 10,
ncol=2)
S14a <- ggdraw()+
draw_plot(p1,0,.05,1,.95)+
draw_plot(legGrob,0,0,1,.05)
p2 <- plot_grid(plts[[7]],plts[[8]],
plts[[9]], plts[[10]],
plts[[11]],plts[[12]],
labels=letters[7:12],label_size = 10,
ncol=2)
S14b <- ggdraw()+
draw_plot(p2,0,.05,1,.95)+
draw_plot(legGrob,0,0,1,.05)
p3 <- plot_grid(plts[[13]],plts[[14]],
plts[[15]], plts[[16]],
plts[[17]],plts[[17]],
labels=letters[13:18],label_size = 10,
ncol=2)
S14c <- ggdraw()+
draw_plot(p3,0,.05,1,.95)+
draw_plot(legGrob,0,0,1,.05)
ggsave(plot = S14a,filename = '../output/S14a.pdf',width = 183,height = 250,units = 'mm',device = cairo_pdf)
ggsave(plot = S14b,filename = '../output/S14b.pdf',width = 183,height = 250,units = 'mm',device = cairo_pdf)
ggsave(plot = S14c,filename = '../output/S14c.pdf',width = 183,height = 250,units = 'mm',device = cairo_pdf)
\ No newline at end of file
3_figures/S01.Rmd
View file @ 7df22ce7
......@@ -55,7 +55,9 @@ Afterwards we use the `S01.R` script to annotate the alignment plot.
```sh
# annotation with R
Rscript --vanilla $WORK/3_figures/S01/S01.R
cd $WORK/3_figures/F_scripts
Rscript --vanilla S01.R
rm Rplots.pdf
```
## Content of circos_figure.R
......
3_figures/S02.Rmd
View file @ 7df22ce7
......@@ -50,8 +50,8 @@ Furthermore, the generation of the outlier annotation changed.
While in the *F~ST~* script, the outlier where determined from the loaded data and later exported, within the G x P script the the highlights don't refer to G x P outliers, but the old *F~ST~* outlier are imported and plotted for reference.
```{r newScript, eval=FALSE}
data2 <- read.csv('fst_outlier_windows.txt', sep='\t')
musks <- read.csv('fst_outlier_ID.txt', sep='\t')
data2 <- read.csv('../../0_data/0_resources/fst_outlier_windows.txt', sep='\t')
musks <- read.csv('../../0_data/0_resources/fst_outlier_ID.txt', sep='\t')
```
This replaced the original section that computes the outlier windows within `F2.R`:
......@@ -152,8 +152,8 @@ data$RUN <- factor(as.character(data$RUN),
levels=c('PN','NU','PU','PPNP','NPUP','PPUP','PBNB','NBUB','PBUB','PHNH','NHUH','PHUH'))
data$COL <- factor(as.character(data$COL),levels=c('PN','PU','NU'))
data2 <- read.csv('fst_outlier_windows.txt', sep='\t')