Commit 097b8c2f authored by mariefbourdon's avatar mariefbourdon
Browse files

220620 narrow peaks freq rec

parent 14db2fc7
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......@@ -1229,29 +1229,53 @@ sd(compar_pos_after$dif_prev,na.rm=TRUE)
```{r}
tab2 %>% filter(exclude_allele==1 & exclude_prop==0) %>% select(marker:n_NA) %>% left_join(.,strains) %>% filter(!parent1 %in% c("N","H") & !parent2 %in% c("N","H"))
# gJAX00038569
newmap_before[["12"]][c("gUNC21523346","gJAX00038569","gUNCHS034222")] #50cM on each side
# mUNC21540855
newmap_before[["12"]][c("gUNCHS034222","mUNC21540855","SFJ123443466")] #50cM on each side
# gUNC21555204
newmap_before[["12"]][c("SFJ123443466","gUNC21555204","gJAX00340618")] #30-60cM on each side
```
```{r}
tab2 %>% filter(exclude_na==1 & exclude_poly==0) %>% select(marker:n_NA)
allele_rec <- tab2 %>% filter(marker %in% c("gJAX00038569","mUNC21540855","gUNC21555204","gUNC21596600")) %>%
select(marker:n_NA) %>% left_join(.,strains,by = c("marker", "chr", "cM_cox"))
# gJAX00038569
newmap_before[["12"]][c("gUNC21523346","gJAX00038569","gUNCHS034222")] #50cM on each side
map_1 <- newmap_before[["12"]][c("gUNC21523346","gJAX00038569","gUNCHS034222")] #50cM on each side
pos_1 <- cross_before[["geno"]][["12"]][["map"]][c("gUNC21523346","gJAX00038569","gUNCHS034222")]
# mUNC21540855
newmap_before[["12"]][c("gUNCHS034222","mUNC21540855","SFJ123443466")] #50cM on each side
map_2 <- newmap_before[["12"]][c("gUNCHS034222","mUNC21540855","SFJ123443466")] #50cM on each side
pos_2 <- cross_before[["geno"]][["12"]][["map"]][c("gUNCHS034222","mUNC21540855","SFJ123443466")]
# gUNC21555204
newmap_before[["12"]][c("SFJ123443466","gUNC21555204","gJAX00340618")] #30-60cM on each side
map_3 <- newmap_before[["12"]][c("SFJ123443466","gUNC21555204","gJAX00340618")] #30-60cM on each side
pos_3 <- cross_before[["geno"]][["12"]][["map"]][c("SFJ123443466","gUNC21555204","gJAX00340618")]
# gUNC21596600
map_4 <- newmap_before[["12"]][c("JAX00341204","gUNC21596600","UNC21601697")] #30-60cM on each side
pos_4 <- cross_before[["geno"]][["12"]][["map"]][c("JAX00341204","gUNC21596600","UNC21601697")]
df <- tibble(gJAX00038569 = c(map_1,pos_1),
mUNC21540855 = c(map_2,pos_2),
gUNC21555204 = c(map_3,pos_3),
gUNC21596600 = c(map_4,pos_4))
df <- as_tibble(cbind(nms = names(df), t(df))) %>% rename(marker = nms,
rec_before = V2,
rec = V3,
rec_after = V4,
pos_before = V5,
pos = V6,
pos_after = V7)
df %<>% mutate(rec_before = as.numeric(rec) - as.numeric(rec_before),
rec_after = as.numeric(rec_after) - as.numeric(rec),
pos_before = as.numeric(pos) - as.numeric(pos_before),
pos_after = as.numeric(pos_after) - as.numeric(pos)) %>%
select(marker,rec_before,rec_after,pos_before,pos_after)
allele_rec <- full_join(allele_rec,df,by="marker") %>% select(marker:parent2,rec_before,rec_after,pos_before,pos_after)
allele_rec
write_csv(allele_rec,"sup/tableS2.csv")
rm(map_1,map_2,map_3,map_4,pos_1,pos_2,pos_3,pos_4,df)
```
```{r}
load("data2/data2_peaks.rda")
load("data3/data3_peaks.rda")
......@@ -1284,7 +1308,100 @@ narrow_grid <- ggdraw() +
c(0,.5,0,.5,0,.35,0,.35,.01,.35,0,.35),c(.96,.96,.8,.8,.64,.615,.48,.45,.32,.30,.16,.162))
narrow_grid
ggsave(narrow_grid,file="narrow_grid.png",width=10,height=17)
ggsave(narrow_grid,file="sup/figureS1.pdf",width=10,height=17)
# Figure S1 : Analysis of the F2 cross data illustrating the identification of spurious narrow non-significant peaks in QTL mappig in 4 data sets.
# A: output of the scanone function of rqtl in a F2 between CC001 and Ifnar KO C57BL/6J showing the identification of 6 narrow non-significant peaks.
# B: output of the scanone function of rqtl in a F2 between Ifnar KO C57BL/6J and Ifnar KO 129S2/SvPas showing the identification of 1 narrow non-significant peak.
# C: output of the scanone function of rqtl in a (CC001xCC071)xCC071 backcross showing no narrow non-significant peak.
# D: output of the scanone function of rqtl in a F2 between Ifnar KO C57BL/6N and CC021 showing the identification of 5 narrow non-significant peaks.
# E: Zoom on Peak 1. Peak 1 is located on a pseudomarker next to a marker with non mendelian proportions (gUNC2731905). F: alleles and genotype proportions for the adjacent markers of Peak 1. Peaks 3, 7, 8 and 9 are also due to a pseudomarkers located next to a markers with non mendelian proportions
# G: Zoom on Peak 6. Peak 6 is located on a marker with non mendelian proportions (SAC132487883). H: alleles and genotype proportions for SAC132487883. Peaks 2, 4 and 12 are also due to a markers with non mendelian proportions.
# I: Zoom on Peak 11. Peak 11 is located on one marker with non mendelian proportions (SAC132487883) and one adjacent pseudomarker. J: alleles and genotype proportions for SAC132487883 and the other adjacent marker to the pseudomarker on the peak. Peak 10 is also due do one marker with non mendelian proportions and one adjacent pseudomarker.
# K: Zoom on Peak 5. Peak 5 is located on a marker showing mendelian proportions (S6J102311553) but in a region with many markers with non mendelian proportions, causing a peak to appear on S6J102311553. L: alleles and genotype proportions for S6J102311553 and the other markers in this region.
```
## Distribution of calculated distance between markers
```{r}
#initialize variables
mark <- c()
chr <- c()
pos <- c()
place <- c()
previous <- c()
follow <- c()
kn_previous <- c()
kn_follow <- c()
#get information in newmap
for(i in names(newmap_before)){
mark <- c(mark,names(newmap_before[[i]]))
chr <- c(chr,rep(i,times=length(newmap_before[[i]])))
pos <- c(pos,unname(newmap_before[[i]]))
place <- c(place,"first",rep("middle",times=(length(newmap_before[[i]])-2)),"last")
prev <- c(NA,unname(newmap_before[[i]])[1:length(newmap_before[[i]])-1])
previous <- c(previous,prev)
fol <- c(unname(newmap_before[[i]])[2:length(newmap_before[[i]])],NA)
follow <- c(follow,fol)
}
#create tab with positions
tab_map1 <- tibble(marker = mark,
chr = chr,
place = place,
pos = pos,
previous = pos-previous,
follow = follow-pos)
tab_map1 %>% ggplot(aes(x=follow)) +
geom_density() +
scale_x_log10()
#initialize variables
mark <- c()
chr <- c()
pos <- c()
place <- c()
previous <- c()
follow <- c()
kn_previous <- c()
kn_follow <- c()
#get information in newmap
for(i in names(newmap_after2)){
mark <- c(mark,names(newmap_after2[[i]]))
chr <- c(chr,rep(i,times=length(newmap_after2[[i]])))
pos <- c(pos,unname(newmap_after2[[i]]))
place <- c(place,"first",rep("middle",times=(length(newmap_after2[[i]])-2)),"last")
prev <- c(NA,unname(newmap_after2[[i]])[1:length(newmap_after2[[i]])-1])
previous <- c(previous,prev)
fol <- c(unname(newmap_after2[[i]])[2:length(newmap_after2[[i]])],NA)
follow <- c(follow,fol)
}
#create tab with positions
tab_map2 <- tibble(marker = mark,
chr = chr,
place = place,
pos = pos,
previous = pos-previous,
follow = follow-pos)
ggplot() +
geom_density(data = tab_map1,aes(x=follow),color="red") +
geom_density(data = tab_map2,aes(x=follow),color="blue") +
scale_x_log10()
ggsave("distrib_freq_rec1.png")
ggplot() +
geom_density(data = tab_map1,aes(x=follow),color="red") +
geom_density(data = tab_map2,aes(x=follow),color="blue") +
scale_x_log10(limits=c(1e-03,1e+05))
ggsave("distrib_freq_rec2.png")
```
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......@@ -206,4 +206,3 @@ rm(none,allele,match,poly,prop)
pheno_before_data3 <- pheno_before_plot
save(pheno_before_data3,file="data3_peaks.rda")
```
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......@@ -367,7 +367,7 @@ peak10 <- qtl_plot(pheno_before,lod=data.frame(group = c("alpha=0.05", "alpha=0.
peak10
```
1 peak on 1 marker and one pseudomarker : S2C102505843 and c10.loc30 in a region with very few markers, postionned between SAH102097335 and S2C102505843.
1 peak on 1 marker and one pseudomarker : S2C102505843 and c10.loc30 postionned between SAH102097335 and S2C102505843.
Here are the infos on genotype counts for these markers:
......
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article/figures/fig1.png

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article/figures/fig1.png

356 KB | W: | H:

article/figures/fig1.png
article/figures/fig1.png
article/figures/fig1.png
article/figures/fig1.png
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marker,chr,cM_cox,allele_1,allele_2,n_HM1,n_HM2,n_HT,n_NA,parent1,parent2,rec_before,rec_after,pos_before,pos_after
gJAX00038569,12,39.58,T,C,28,85,63,0,C,C,49.51085190700178,51.76929638840011,0.4069999999999965,0.05100000000000193
mUNC21540855,12,39.8,A,C,27,84,65,0,C,C,51.32978371999707,49.47180925500288,0.16899999999999693,0.38300000000000267
gUNC21555204,12,40.946,T,C,84,27,65,0,T,T,31.93935668369886,57.1188112419004,0.7629999999999981,0.38400000000000034
gUNC21596600,12,44.084,A,G,87,26,61,2,A,A,148.75752846560135,25.47917970369963,0.03800000000000381,0.1839999999999975
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