FigS_wholeGenomeScan.Rmd

---
title: "Data analysis"
author: "Aoyue Bi, Daxing Xu"
date: "`r Sys.Date()`"
output: 
  html_document: # html_notebook, html_document
    toc: true
    toc_float:
      toc_collapsed: true
    toc_depth: 3
    number_sections: true
    theme: simplex # default, united, cerulean, journal, flatly, darkly, readable, spacelab, united, cosmo, lumen, paper, sandstone, simplex, and yeti
    highlight: haddock # default, tango, pygments, kate, monochrome, espresso, zenburn, haddock, and breezedark
    # bibliography: bibliography.json
---


# FigS

```{r setup, echo =T, message = T, warning = F}
library(tidyverse)
# library(RColorBrewer)
library(ggpubr)
# library(egg)
## eval 代码要不要运行
## echo 代码要不要输出
## include 图要不要输出
## warning 警告要不要输出
## message 默认Bin等信息要不要输出
```


##  SNP distribution on the whole genome
```{r}
df <- read_tsv("data/018_wholeGenomeScan/vmap2.1.posAllele_10000000window_1000000step.txt.gz")

max(df$Count)
min(df$Count)

# ## 写出 circos
# dfout <- df %>% 
#   mutate(BIN_START=)
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/001_snpDensity.txt",col_names = F)

data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=Count/10000))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000), y= 3/40000 *max(df$Count)), 
            size=2.5)+
  labs(x="Physical position (Mb)", y = "SNP count on the whole-genome (x10000)")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  scale_y_continuous(limits = c(0,30))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))

p

# ggsave(p,filename = "~/Documents/test.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/test.pdf",height =3.6, width = 7.2)

```

## 计数 on the whole genome
```{r}
df <- read_tsv("data/018_wholeGenomeScan/vmap2.1.posAllele_10000000window_1000000step.txt.gz")

df_ave <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  group_by(Sub) %>% 
  summarise(ave=mean(Count))

max(df$Count)
min(df$Count)



```



##  SNP distribution on the gene region
```{r}
df <- read_tsv("data/018_wholeGenomeScan/003_gene_SNP_10000000window_1000000step.txt.gz")

max(df$Count)
min(df$Count)

data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

# ### 写出 circos
# dfout <- df %>% select(CHROM,BIN_START,BIN_END,Count)
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/002_gene_snpDensity.txt",col_names = F)

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=Count))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000), y= 3/4 *max(df$Count)), 
            size=2.5)+
  labs(x="Physical position (Mb)", y = "SNP count on the gene region")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  scale_y_continuous(limits = c(0,9000),breaks = c(0,2500,5000,7500))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))

p

# ggsave(p,filename = "~/Documents/SNPcount_geneRegion.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/SNPcount_geneRegion.pdf",height =3.6, width = 7.2)


# df %>% ggplot(aes(x=df$Count))+
#   geom_histogram()
#   facet_wrap(~CHROM,ncol = 3)
```



## GERP
```{r}
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/002_GERP/007_merge006/GERP_more0_10000000window_1000000step.txt.gz") %>% 
#   filter(!is.na(Ave), is.finite(Ave))

df <- read_tsv("data/018_wholeGenomeScan/GERP_10000000window_1000000step.txt.gz") %>% 
  filter(!is.na(Ave), is.finite(Ave))

max(df$Ave)
min(df$Ave)

# dfout <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/002_GERP/009_merge008/GERP_10000000window_1000000step.txt.gz") %>% 
#   filter(!is.na(Ave), is.finite(Ave)) %>% 
#   filter(Ave <= 0.08)
# 
# ### 写出 circos
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,Ave) %>% 
#   mutate(Ave=format(Ave,scientific = FALSE)) %>% 
#   mutate(Ave=str_replace_all(Ave," ",""))
# 
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/003_GERP.txt",col_names = F)

data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=Ave))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000), 
                y=0.06
                # y= 3/4 *max(df$Ave)
                ), 
            size=2.5)+
  labs(x="Physical position (Mb)", y = "GERP score")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  # scale_y_continuous(limits = c(0.4,1.05))+
  scale_y_continuous(breaks = c(0,0.03,0.06,0.09))+
  coord_cartesian(ylim = c(0,0.1))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))

p

# ggsave(p,filename = "~/Documents/test.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/GERP_wholeGenomeScan.pdf",height =3.6, width = 7.2)

```

## PPH2
```{r}
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/002_GERP/007_merge006/GERP_more0_10000000window_1000000step.txt.gz") %>% 
#   filter(!is.na(Ave), is.finite(Ave))

df <- read_tsv("data/018_wholeGenomeScan/003_PPH2_10000000window_1000000step.txt.gz") %>% 
  filter(!is.na(Ave), is.finite(Ave))

max(df$Ave)
min(df$Ave)

# ### 写出 circos
# dfout <- df %>% select(CHROM,BIN_START,BIN_END,Ave) %>% 
#   mutate(Ave=format(Ave,scientific = FALSE)) %>% 
#   mutate(Ave=str_replace_all(Ave," ",""))
# 
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/004_PPH2.txt",col_names = F)

data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=Ave))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000), 
                y=0.6
                # y= 3/4 *max(df$Ave)
                ), 
            size=2.5)+
  labs(x="Physical position (Mb)", y = "PPH2 score")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  # scale_y_continuous(limits = c(0.4,1.05))+
  scale_y_continuous(breaks = c(0,0.3,0.6,0.9))+
  coord_cartesian(ylim = c(0,1))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))

p

# ggsave(p,filename = "~/Documents/test.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/PPH2_wholeGenomeScan.pdf",height =3.6, width = 7.2)

```


#### ============
## Whole genome scan
### DelSynRatio
```{r}
df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>%
  filter(!is.na(DelSynRatio))


# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(DelSynRatio),is.finite(DelSynRatio))
# 
# max(df$DelSynRatio)
# min(df$DelSynRatio)
# 
# # ### 写出 circos
# dfout <- df %>%
#   filter(!is.na(DelSynRatio), is.finite(DelSynRatio)) %>%
#   filter(DelSynRatio <= 1.3)
# 
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,DelSynRatio) %>%
#   mutate(DelSynRatio=format(DelSynRatio,scientific = FALSE)) %>%
#   mutate(DelSynRatio=str_replace_all(DelSynRatio," ",""))
# 
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/005_DelSynRatio.txt",col_names = F)




#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=DelSynRatio))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000),
          # y= 3/4 *max(df$DelSynRatio) 
            y=1.5
            ),
            size=2.5)+
  labs(x="Physical position (Mb)", y = "DelRatio")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  # scale_y_continuous(limits = c(0,4))+
  coord_cartesian(ylim = c(0,2))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))
p

ggsave(p,filename = "~/Documents/01-DelSynRatio.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")

```

### NonsynSynRatio
```{r}

df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>% 
  filter(!is.na(NonsynSynRatio)) %>% 
  filter(is.finite(NonsynSynRatio))

# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(NonsynSynRatio)) %>% 
#   filter(is.finite(NonsynSynRatio))
# 
# ### 0-4
# max(df$NonsynSynRatio)
# min(df$NonsynSynRatio)
# 
# # ### 写出 circos
# dfout <- df %>%
#   filter(!is.na(NonsynSynRatio), is.finite(NonsynSynRatio)) %>%
#   filter(NonsynSynRatio <= 3)
# 
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,NonsynSynRatio) %>%
#   mutate(NonsynSynRatio=format(NonsynSynRatio,scientific = FALSE)) %>%
#   mutate(NonsynSynRatio=str_replace_all(NonsynSynRatio," ",""))
# 
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/006_NonsynSynRatio.txt",col_names = F)


# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>% 
  # filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=NonsynSynRatio))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000),
          # y= 3/4 *max(df$DelSynRatio) 
            y=3
            ),
            size=2.5)+
  labs(x="Physical position (Mb)", y = "NonsynSynRatio")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  # scale_y_continuous(limits = c(0,4))+
  scale_y_continuous(breaks = c(0,2,4))+
  coord_cartesian(ylim = c(0,4))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))
p

ggsave(p,filename = "~/Documents/02-NonsynSynRatio.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")
```


### DelFre
```{r}

df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>% 
  filter(!is.na(DelFre)) %>% 
  filter(is.finite(DelFre))

### 0-4
max(df$DelFre)
min(df$DelFre)

# ### 写出 circos
# dfout <- df %>%
#   filter(!is.na(DelFre), is.finite(DelFre)) %>% 
#   filter(DelFre != 0)
# 
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,DelFre) %>%
#   mutate(DelFre=format(DelFre,scientific = FALSE)) %>%
#   mutate(DelFre=str_replace_all(DelFre," ",""))
# 
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/007_DelFre.txt",col_names = F)

# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>% 
  # filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=DelFre))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000),
          # y= 3/4 *max(df$DelSynRatio) 
            y=0.0015
            ),
            size=2.5)+
  labs(x="Physical position (Mb)", y = "DelFre")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  # scale_y_continuous(limits = c(0,4))+
  scale_y_continuous(breaks = c(0,0.001,0.002))+
  coord_cartesian(ylim = c(0,0.0025))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))
p

ggsave(p,filename = "~/Documents/03-DelFre.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")
```


### NonsynFre
```{r}

df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>% 
  filter(!is.na(NonsynFre)) %>% 
  filter(is.finite(NonsynFre))

### 0-4
max(df$NonsynFre)
min(df$NonsynFre)


# # ### 写出 circos
# dfout <- df %>%
#   filter(!is.na(NonsynFre), is.finite(NonsynFre)) %>%
#   filter(NonsynFre != 0)
# 
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,NonsynFre) %>%
#   mutate(NonsynFre=format(NonsynFre,scientific = FALSE)) %>%
#   mutate(NonsynFre=str_replace_all(NonsynFre," ",""))
# 
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/008_NonsynFre.txt",col_names = F)


# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>% 
  # filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=NonsynFre))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000),
          # y= 3/4 *max(df$DelSynRatio) 
            y=0.006
            ),
            size=2.5)+
  labs(x="Physical position (Mb)", y = "NonsynFre")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  # scale_y_continuous(limits = c(0,4))+
  scale_y_continuous(breaks = c(0,0.004,0.008))+
  coord_cartesian(ylim = c(0,0.009))+
  
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))
p

ggsave(p,filename = "~/Documents/04-NonsynFre.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")
```



### SynFre
```{r}

df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>% 
  filter(!is.na(SynFre)) %>% 
  filter(is.finite(SynFre))

### 0-4
max(df$SynFre)
min(df$SynFre)


# # # ### 写出 circos
# dfout <- df %>%
#   filter(!is.na(SynFre), is.finite(SynFre)) %>%
#   filter(SynFre != 0)
# 
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,SynFre) %>%
#   mutate(SynFre=format(SynFre,scientific = FALSE)) %>%
#   mutate(SynFre=str_replace_all(SynFre," ",""))
# 
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/009_SynFre.txt",col_names = F)


# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>% 
  # filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)

colB <- c("#fd8582","#967bce","#4bcdc6")

p <- df %>% 
  mutate(Sub=str_sub(CHROM,2,2)) %>% 
  ggplot(aes(x=BIN_START/1000000, y=SynFre))+
  geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
  geom_area(alpha=0.8,aes(fill=Sub)) +
  geom_point(aes(x,y),color = "blue",size=1,data = data)+
  geom_text(data = tibble(CHROM = unique(df$CHROM)),
            aes(label = CHROM, x=median(df$BIN_START/1000000),
          # y= 3/4 *max(df$DelSynRatio) 
            y=0.005
            ),
            size=2.5)+
  labs(x="Physical position (Mb)", y = "SynFre")+
  scale_fill_manual(values = colB)+
  scale_color_manual(values = colB)+
  facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
  # scale_y_continuous(limits = c(0,4))+
  scale_y_continuous(breaks = c(0,0.004,0.008))+
  coord_cartesian(ylim = c(0,0.009))+
  theme_classic()+
  theme(panel.grid = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(size=0.3, colour = "black"),
    legend.position = 'none',
    strip.text = element_blank(),
    text = element_text(size = 9))
p

ggsave(p,filename = "~/Documents/05-SynFre.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")
```


#### =============
## 运行 circos
circos -conf circosByAoyue.conf -outputdir ./