220620 narrow peaks freq rec

article/article_figures.Rmd

@@ -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")
 ```
 

article/data3/data3.Rmd

@@ -206,4 +206,3 @@ rm(none,allele,match,poly,prop)
 pheno_before_data3 <- pheno_before_plot
 save(pheno_before_data3,file="data3_peaks.rda")
 ```
-

article/data4/data4.Rmd

@@ -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:
 

article/sup/tableS2.csv

+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