diff --git a/article/.RData b/article/.RData
index c0be9003d44b0570135bb255d8094d5c06fa8b9f..b237688b25f49dd8a8017e3c9ad0bb9ad54821f2 100644
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diff --git a/article/article_figures.Rmd b/article/article_figures.Rmd
index f22df32c0c4ac8a6bfc4333741b3cff224b5a199..047b893c1371be614febd7b6bf64d7d6c7f873ff 100644
--- a/article/article_figures.Rmd
+++ b/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")
```
diff --git a/article/data2/.RData b/article/data2/.RData
index eda0e03052997e2a704fbe6c3976e57ba3c2c2f7..cdbdc44bd2f33c59f73064c3b0e6630810b3aa5f 100644
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diff --git a/article/data3/.RData b/article/data3/.RData
index 8be84ee35d189aebb25b3ea652a46f118edafee1..91508616405e2f4a42f8c67ba69f51195b118a14 100644
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diff --git a/article/data3/data3.Rmd b/article/data3/data3.Rmd
index d525b578241e8973eaa1a6713090f9613ee97ed2..e13d1d6a56b988d94d4fe329eb98d510ae5da684 100644
--- a/article/data3/data3.Rmd
+++ b/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")
```
-
diff --git a/article/data4/.RData b/article/data4/.RData
index 9da838548717419c9e723960988b2a3672bf1503..96e827029804e161b294602b21079894580e065c 100644
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diff --git a/article/data4/data4.Rmd b/article/data4/data4.Rmd
index 1b6938eb82c6d82211608c835f8b9faf23503a37..a00da46764565e725d40424f3737b96b61bfe858 100644
--- a/article/data4/data4.Rmd
+++ b/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:
diff --git a/article/distrib_freq_rec1.png b/article/distrib_freq_rec1.png
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diff --git a/article/narrow_grid.png b/article/narrow_grid.png
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diff --git a/article/sup/figureS1.pdf b/article/sup/figureS1.pdf
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diff --git a/article/sup/tableS2.csv b/article/sup/tableS2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3bf00a6006afea6c53a620f808866e9e53a13ebd
--- /dev/null
+++ b/article/sup/tableS2.csv
@@ -0,0 +1,5 @@
+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