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Commit 5d0a519c authored by mariefbourdon's avatar mariefbourdon
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modifs mark_estmap for first/last groups

parent 90b4fadf
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1 merge request!9Develop
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with 197 additions and 188 deletions
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build-last-errors-base-dir="~/Documents/PhD/stuart_package/stuart/"
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/Users/mariebourdon/Documents/PhD/stuart_package/stuart/DESCRIPTION="5140B408"
/Users/mariebourdon/Documents/PhD/stuart_package/stuart/R/geno_strains.R="EBA82473"
/Users/mariebourdon/Documents/PhD/stuart_package/stuart/R/mark_allele.R="A0A182D3"
/Users/mariebourdon/Documents/PhD/stuart_package/stuart/R/mark_estmap.R="57E1825F"
/Users/mariebourdon/Documents/PhD/stuart_package/stuart/R/mark_match.R="FFA1BE52"
/Users/mariebourdon/Documents/PhD/stuart_package/stuart/R/mark_prop.R="30FA9E8C"
/Users/mariebourdon/Documents/PhD/stuart_package/stuart/R/tab_mark.R="F0B2417"
/Users/mariebourdon/Documents/PhD/stuart_package/stuart/R/write_rqtl.R="F07CE16C"
......
......@@ -87,12 +87,17 @@ mark_estmap <- function(tab,map,annot,d=20,r=10,n=5){
T ~ group))
new_pos <- match("new",tab_chr$group)
g <- g+1
}
tab_chr <- tab_chr %>% tidyr::fill(group)
tab_chr <- tab_chr %>% mutate(group=as.numeric(group)) %>% select(-row)
summa <- tab_chr %>% group_by(group) %>% summarise(n=n())
gremove <- summa %>% filter(n<10) %>% select(group) %>% pull()
summa <- tab_chr %>% group_by(group) %>% summarise(N=n())
summa <- summa %>% mutate(n_bef=lag(N,default=9))
summa <- summa %>% mutate(n_af=lead(N,default=9))
summa <- summa %>% mutate(excl=case_when(N<n ~ 1,
T ~ 0))
summa <- summa %>% mutate(ex_bef=lag(excl,default=9))
summa <- summa %>% mutate(ex_af=lead(excl,default=9))
gremove <- summa %>% filter(excl==1 & ((ex_bef!=1 & ex_af!=1) | (ex_bef!=9 & ex_af!=9))) %>% select(group) %>% pull()
mark_remove <- bind_rows(mark_remove,tab_chr %>% filter(group %in% gremove))
}
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......@@ -361,7 +361,7 @@ plotmap_after <- ~plotMap(cross_after,newmap_after,shift=TRUE,main="After stuart
```{r after_estmap}
#filter with mark_estmap
tab2 <- mark_estmap(tab2,newmap_after)
tab2 <- mark_estmap(tab2,newmap_after,annot_mini)
# create rqtl csv file
write_rqtl(geno=genos,pheno=phenos,tab=tab2,ref=strains,par1="parent1",par2="parent2",prefix="ind_",pos="cM_cox",path="files/cluster2/cross_after.csv")
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--Read the following data:
176 individuals
2236 markers
2235 markers
4 phenotypes
--Cross type: f2
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% latex table generated in R 4.0.4 by xtable 1.8-4 package
% Mon Jan 3 17:04:48 2022
% Tue Jan 4 10:53:15 2022
\begin{table}[ht]
\centering
\begin{tabular}{lllllrrr}
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