Nothing
inst/doc/Vignette_genotype_probabilities.R
In polymapR: Linkage Analysis in Outcrossing Polyploids
## ---- eval = FALSE------------------------------------------------------------
# install.packages("polymapR")
# library(polymapR)
## ---- eval = FALSE------------------------------------------------------------
# geno <- read.csv("fitPoly_4x_output_2343_SNPs.csv")
## ---- echo = FALSE------------------------------------------------------------
library(polymapR)
load("genoprobsdata.RData")
## ---- eval = FALSE------------------------------------------------------------
# knitr::kable(head(geno))
## ---- echo = FALSE------------------------------------------------------------
knitr::kable(head(geno.sub))
## ---- eval = FALSE------------------------------------------------------------
# parent1.reps <- c("P1","P1a")
# parent2.reps <- "P2"
# individuals <- setdiff(unique(geno$SampleName),c(parent1.reps,parent2.reps))
## ---- eval = FALSE------------------------------------------------------------
# chk1 <- checkF1(input_type = "probabilistic",
# probgeno_df = geno,
# parent1 = parent1.reps,
# parent2 = parent2.reps,
# F1 = individuals,
# polysomic = TRUE,
# disomic = FALSE,
# mixed = FALSE,
# ploidy = 4)
## ---- eval = FALSE------------------------------------------------------------
# chk1$checked_F1[1:5,]
## ---- echo = FALSE------------------------------------------------------------
chk1.sub[1:5,]
## ---- eval = FALSE------------------------------------------------------------
# pardose <- polymapR:::assign_parental_dosage(chk = chk1,
# probgeno_df = geno)
# knitr::kable(head(pardose))
## ---- echo = FALSE------------------------------------------------------------
knitr::kable(head(pardose.sub))
## ---- eval = FALSE------------------------------------------------------------
# length(which(chk1$checked_F1$qall_mult == 0)) #859 markers
## ---- eval = FALSE------------------------------------------------------------
# remove.mark <- chk1$checked_F1[chk1$checked_F1$qall_mult==0,"MarkerName"]
# geno1 <- geno[!geno$MarkerName %in% remove.mark,]
## ---- eval = FALSE------------------------------------------------------------
# gpo <- gp_overview(probgeno_df = geno1)
## ---- out.width = "500px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/gp_overview.png")
## ---- eval = FALSE------------------------------------------------------------
# geno1 <- gpo$probgeno_df
## ---- eval = FALSE------------------------------------------------------------
# maxP.chk <- check_maxP(probgeno_df = geno1)
## ---- echo = FALSE------------------------------------------------------------
print(maxP.chk)
## ---- out.width = "550px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/maxPdist.png")
## ---- eval = FALSE------------------------------------------------------------
# geno2 <- screen_for_duplicate_individuals.gp(probgeno_df = geno1,
# ploidy = 4,
# parent1 = parent1.reps,
# parent2 = parent2.reps,
# F1 = individuals)
## ---- out.width = "550px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/dup_indivs.png")
## ---- echo = FALSE------------------------------------------------------------
write("\nNo duplicates found\n",stdout())
## -----------------------------------------------------------------------------
nc <- parallel::detectCores() - 2
## ---- eval = FALSE------------------------------------------------------------
# chk1 <- checkF1(input_type = "probabilistic",
# probgeno_df = geno2,
# parent1 = parent1.reps,
# parent2 = parent2.reps,
# F1 = individuals,
# polysomic = TRUE,
# disomic = FALSE,
# mixed = FALSE,
# ploidy = 4)
## ---- eval = FALSE------------------------------------------------------------
# SN_SN_P1 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# target_parent = "P1",
# LOD_threshold = 3,
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# head(SN_SN_P1)
## ---- echo = FALSE------------------------------------------------------------
head(SN_SN_P1.sub)
## ---- eval = FALSE------------------------------------------------------------
# par(mfrow = c(2,1))
# P1_homologues <- cluster_SN_markers(linkage_df = SN_SN_P1,
# LOD_sequence = seq(3,12,0.5),
# LG_number = 5,
# ploidy = 4,
# parentname = "P1",
# plot_clust_size = FALSE,
# min_clust_size = 3)
## ---- out.width = "600px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/p1_clustering_gp.png")
## -----------------------------------------------------------------------------
sort(table(P1_homologues[['7']]$cluster),decreasing = T)
length(table(P1_homologues[['7']]$cluster))
## ---- eval = FALSE------------------------------------------------------------
# SN_SN_P2 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# target_parent = "P2",
# LOD_threshold = 3,
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# P2_homologues <- cluster_SN_markers(linkage_df = SN_SN_P2,
# LOD_sequence = seq(3,12,0.5),
# LG_number = 5,
# ploidy = 4,
# parentname = "P2",
# plot_clust_size = F,
# min_clust_size = 3)
## ---- out.width = "600px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/p2_clustering_gp.png")
## -----------------------------------------------------------------------------
sort(table(P2_homologues[['6']]$cluster),decreasing = T)
length(table(P2_homologues[['6']]$cluster))
## ---- eval = FALSE------------------------------------------------------------
# SN_SS_P1 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# markertype2 = c(1,1),
# target_parent = "P1",
# ncores = nc)
#
# SN_SS_P2 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# markertype2 = c(1,1),
# target_parent = "P2",
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# LGHomDf_P1 <- bridgeHomologues(cluster_stack = P1_homologues[["7"]],
# cluster_stack2 = P2_homologues[["7"]],
# linkage_df = SN_SS_P1,
# linkage_df2 = SN_SS_P2,
# LOD_threshold = 5,
# LG_number = 5)
## ---- out.width = "450px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/P1_bridges.png")
## -----------------------------------------------------------------------------
table(LGHomDf_P1$LG,LGHomDf_P1$homologue)
## ---- eval = FALSE------------------------------------------------------------
# LGHomDf_P2 <- bridgeHomologues(cluster_stack = P2_homologues[["6"]],
# cluster_stack2 = P1_homologues[["6"]],
# linkage_df = SN_SS_P2,
# linkage_df2 = SN_SS_P1,
# LOD_threshold = 5,
# LG_number = 5)
## ---- out.width = "450px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/P2_bridges.png")
## -----------------------------------------------------------------------------
table(LGHomDf_P2$LG,LGHomDf_P2$homologue)
## ---- eval = FALSE------------------------------------------------------------
# LGHomDf_P1a <-cluster_per_LG(LG = 3,
# linkage_df = SN_SN_P1[SN_SN_P1$phase == "coupling",],
# LG_hom_stack = LGHomDf_P1,
# LOD_sequence = 3:10,
# modify_LG_hom_stack = TRUE,
# network.layout = "stacked",
# nclust_out = 4,
# label.offset=1.2)
## ---- out.width = "450px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/cluster_per_LG_P1.3.png")
## -----------------------------------------------------------------------------
table(LGHomDf_P1a$LG,LGHomDf_P1a$homologue)
## -----------------------------------------------------------------------------
head(LGHomDf_P1a)
## ---- eval = FALSE------------------------------------------------------------
# P1_SxS_Assigned <- assign_linkage_group(linkage_df = SN_SS_P1,
# LG_hom_stack = LGHomDf_P1a,
# SN_colname = "marker_a",
# unassigned_marker_name = "marker_b",
# phase_considered = "coupling",
# LG_number = 5,
# LOD_threshold = 3,
# ploidy = 4)
#
# P2_SxS_Assigned <- assign_linkage_group(linkage_df = SN_SS_P2,
# LG_hom_stack = LGHomDf_P2,
# SN_colname = "marker_a",
# unassigned_marker_name = "marker_b",
# phase_considered = "coupling",
# LG_number = 5,
# LOD_threshold = 3,
# ploidy = 4)
## -----------------------------------------------------------------------------
LGHomDf_P2c <- consensus_LG_names(modify_LG = LGHomDf_P2,
template_SxS = P1_SxS_Assigned,
modify_SxS = P2_SxS_Assigned)
## ---- eval = FALSE------------------------------------------------------------
# save(LGHomDf_P1a,LGHomDf_P2c, file = "LGHomDf_stacks.Rdata") #for example..
## ---- eval = FALSE------------------------------------------------------------
# P2_SxS_Assigned <- assign_linkage_group(linkage_df = SN_SS_P2,
# LG_hom_stack = LGHomDf_P2c, #this is changed
# SN_colname = "marker_a",
# unassigned_marker_name = "marker_b",
# phase_considered = "coupling",
# LG_number = 5,
# LOD_threshold = 3,
# ploidy = 4)
## ---- eval = FALSE------------------------------------------------------------
# marker_assignments_P1 <- homologue_lg_assignment(input_type = "probabilistic",
# probgeno_df = geno2,
# chk = chk1,
# assigned_list = list(P1_SxS_Assigned),
# assigned_markertypes = list(c(1,1)),
# LG_hom_stack = LGHomDf_P1a,
# target_parent = "P1",
# other_parent = "P2",
# ploidy = 4,
# pairing = "random",
# convert_palindrome_markers = FALSE,
# LG_number = 5,
# LOD_threshold = 3,
# write_intermediate_files = FALSE)
#
# marker_assignments_P2 <- homologue_lg_assignment(input_type = "probabilistic",
# probgeno_df = geno2,
# chk = chk1,
# assigned_list = list(P2_SxS_Assigned),
# assigned_markertypes = list(c(1,1)),
# LG_hom_stack = LGHomDf_P2c,
# target_parent = "P2",
# other_parent = "P1",
# ploidy = 4,
# pairing = "random",
# convert_palindrome_markers = FALSE,
# LG_number = 5,
# LOD_threshold = 3,
# write_intermediate_files = FALSE)
## ---- eval = FALSE------------------------------------------------------------
# marker_assignments <- check_marker_assignment(marker_assignments_P1,marker_assignments_P2)
## ---- eval = FALSE------------------------------------------------------------
# saveRDS(marker_assignments, file = "marker_assignments.RDS")
## ---- eval = FALSE------------------------------------------------------------
# all_linkages_list_P1 <- finish_linkage_analysis(input_type = "probabilistic",
# marker_assignment = marker_assignments$P1,
# probgeno_df = geno2,
# chk = chk1,
# target_parent = "P1",
# other_parent = "P2",
# convert_palindrome_markers = FALSE,
# ploidy = 4,
# pairing = "random",
# LG_number = 5,
# ncores = nc)
#
# all_linkages_list_P2 <- finish_linkage_analysis(input_type = "probabilistic",
# marker_assignment = marker_assignments$P2,
# probgeno_df = geno2,
# chk = chk1,
# target_parent = "P2",
# other_parent = "P1",
# convert_palindrome_markers = TRUE,
# ploidy = 4,
# pairing = "random",
# LG_number = 5,
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# linkages <- list()
# for(lg in names(all_linkages_list_P1)){
# linkages[[lg]] <- rbind(all_linkages_list_P1[[lg]], all_linkages_list_P2[[lg]])
# }
## ---- eval = FALSE------------------------------------------------------------
# saveRDS(linkages, file = "linkages.RDS")
## ---- eval = FALSE------------------------------------------------------------
# linkages <- readRDS("linkages.RDS")
## ---- eval = FALSE------------------------------------------------------------
# integrated.maplist <- MDSMap_from_list(linkages)
## ---- eval = FALSE------------------------------------------------------------
# phased.maplist <- create_phased_maplist(input_type = "probabilistic",
# maplist = integrated.maplist,
# chk = chk1,
# ploidy = 4,
# marker_assignment.1 = marker_assignments$P1,
# marker_assignment.2 = marker_assignments$P2)
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## ---- eval = FALSE------------------------------------------------------------
# install.packages("polymapR")
# library(polymapR)
## ---- eval = FALSE------------------------------------------------------------
# geno <- read.csv("fitPoly_4x_output_2343_SNPs.csv")
## ---- echo = FALSE------------------------------------------------------------
library(polymapR)
load("genoprobsdata.RData")
## ---- eval = FALSE------------------------------------------------------------
# knitr::kable(head(geno))
## ---- echo = FALSE------------------------------------------------------------
knitr::kable(head(geno.sub))
## ---- eval = FALSE------------------------------------------------------------
# parent1.reps <- c("P1","P1a")
# parent2.reps <- "P2"
# individuals <- setdiff(unique(geno$SampleName),c(parent1.reps,parent2.reps))
## ---- eval = FALSE------------------------------------------------------------
# chk1 <- checkF1(input_type = "probabilistic",
# probgeno_df = geno,
# parent1 = parent1.reps,
# parent2 = parent2.reps,
# F1 = individuals,
# polysomic = TRUE,
# disomic = FALSE,
# mixed = FALSE,
# ploidy = 4)
## ---- eval = FALSE------------------------------------------------------------
# chk1$checked_F1[1:5,]
## ---- echo = FALSE------------------------------------------------------------
chk1.sub[1:5,]
## ---- eval = FALSE------------------------------------------------------------
# pardose <- polymapR:::assign_parental_dosage(chk = chk1,
# probgeno_df = geno)
# knitr::kable(head(pardose))
## ---- echo = FALSE------------------------------------------------------------
knitr::kable(head(pardose.sub))
## ---- eval = FALSE------------------------------------------------------------
# length(which(chk1$checked_F1$qall_mult == 0)) #859 markers
## ---- eval = FALSE------------------------------------------------------------
# remove.mark <- chk1$checked_F1[chk1$checked_F1$qall_mult==0,"MarkerName"]
# geno1 <- geno[!geno$MarkerName %in% remove.mark,]
## ---- eval = FALSE------------------------------------------------------------
# gpo <- gp_overview(probgeno_df = geno1)
## ---- out.width = "500px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/gp_overview.png")
## ---- eval = FALSE------------------------------------------------------------
# geno1 <- gpo$probgeno_df
## ---- eval = FALSE------------------------------------------------------------
# maxP.chk <- check_maxP(probgeno_df = geno1)
## ---- echo = FALSE------------------------------------------------------------
print(maxP.chk)
## ---- out.width = "550px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/maxPdist.png")
## ---- eval = FALSE------------------------------------------------------------
# geno2 <- screen_for_duplicate_individuals.gp(probgeno_df = geno1,
# ploidy = 4,
# parent1 = parent1.reps,
# parent2 = parent2.reps,
# F1 = individuals)
## ---- out.width = "550px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/dup_indivs.png")
## ---- echo = FALSE------------------------------------------------------------
write("\nNo duplicates found\n",stdout())
## -----------------------------------------------------------------------------
nc <- parallel::detectCores() - 2
## ---- eval = FALSE------------------------------------------------------------
# chk1 <- checkF1(input_type = "probabilistic",
# probgeno_df = geno2,
# parent1 = parent1.reps,
# parent2 = parent2.reps,
# F1 = individuals,
# polysomic = TRUE,
# disomic = FALSE,
# mixed = FALSE,
# ploidy = 4)
## ---- eval = FALSE------------------------------------------------------------
# SN_SN_P1 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# target_parent = "P1",
# LOD_threshold = 3,
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# head(SN_SN_P1)
## ---- echo = FALSE------------------------------------------------------------
head(SN_SN_P1.sub)
## ---- eval = FALSE------------------------------------------------------------
# par(mfrow = c(2,1))
# P1_homologues <- cluster_SN_markers(linkage_df = SN_SN_P1,
# LOD_sequence = seq(3,12,0.5),
# LG_number = 5,
# ploidy = 4,
# parentname = "P1",
# plot_clust_size = FALSE,
# min_clust_size = 3)
## ---- out.width = "600px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/p1_clustering_gp.png")
## -----------------------------------------------------------------------------
sort(table(P1_homologues[['7']]$cluster),decreasing = T)
length(table(P1_homologues[['7']]$cluster))
## ---- eval = FALSE------------------------------------------------------------
# SN_SN_P2 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# target_parent = "P2",
# LOD_threshold = 3,
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# P2_homologues <- cluster_SN_markers(linkage_df = SN_SN_P2,
# LOD_sequence = seq(3,12,0.5),
# LG_number = 5,
# ploidy = 4,
# parentname = "P2",
# plot_clust_size = F,
# min_clust_size = 3)
## ---- out.width = "600px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/p2_clustering_gp.png")
## -----------------------------------------------------------------------------
sort(table(P2_homologues[['6']]$cluster),decreasing = T)
length(table(P2_homologues[['6']]$cluster))
## ---- eval = FALSE------------------------------------------------------------
# SN_SS_P1 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# markertype2 = c(1,1),
# target_parent = "P1",
# ncores = nc)
#
# SN_SS_P2 <- linkage.gp(probgeno_df = geno2,
# chk = chk1,
# markertype1 = c(1,0),
# markertype2 = c(1,1),
# target_parent = "P2",
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# LGHomDf_P1 <- bridgeHomologues(cluster_stack = P1_homologues[["7"]],
# cluster_stack2 = P2_homologues[["7"]],
# linkage_df = SN_SS_P1,
# linkage_df2 = SN_SS_P2,
# LOD_threshold = 5,
# LG_number = 5)
## ---- out.width = "450px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/P1_bridges.png")
## -----------------------------------------------------------------------------
table(LGHomDf_P1$LG,LGHomDf_P1$homologue)
## ---- eval = FALSE------------------------------------------------------------
# LGHomDf_P2 <- bridgeHomologues(cluster_stack = P2_homologues[["6"]],
# cluster_stack2 = P1_homologues[["6"]],
# linkage_df = SN_SS_P2,
# linkage_df2 = SN_SS_P1,
# LOD_threshold = 5,
# LG_number = 5)
## ---- out.width = "450px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/P2_bridges.png")
## -----------------------------------------------------------------------------
table(LGHomDf_P2$LG,LGHomDf_P2$homologue)
## ---- eval = FALSE------------------------------------------------------------
# LGHomDf_P1a <-cluster_per_LG(LG = 3,
# linkage_df = SN_SN_P1[SN_SN_P1$phase == "coupling",],
# LG_hom_stack = LGHomDf_P1,
# LOD_sequence = 3:10,
# modify_LG_hom_stack = TRUE,
# network.layout = "stacked",
# nclust_out = 4,
# label.offset=1.2)
## ---- out.width = "450px", echo = FALSE, fig.align="center"-------------------
knitr::include_graphics("figures/cluster_per_LG_P1.3.png")
## -----------------------------------------------------------------------------
table(LGHomDf_P1a$LG,LGHomDf_P1a$homologue)
## -----------------------------------------------------------------------------
head(LGHomDf_P1a)
## ---- eval = FALSE------------------------------------------------------------
# P1_SxS_Assigned <- assign_linkage_group(linkage_df = SN_SS_P1,
# LG_hom_stack = LGHomDf_P1a,
# SN_colname = "marker_a",
# unassigned_marker_name = "marker_b",
# phase_considered = "coupling",
# LG_number = 5,
# LOD_threshold = 3,
# ploidy = 4)
#
# P2_SxS_Assigned <- assign_linkage_group(linkage_df = SN_SS_P2,
# LG_hom_stack = LGHomDf_P2,
# SN_colname = "marker_a",
# unassigned_marker_name = "marker_b",
# phase_considered = "coupling",
# LG_number = 5,
# LOD_threshold = 3,
# ploidy = 4)
## -----------------------------------------------------------------------------
LGHomDf_P2c <- consensus_LG_names(modify_LG = LGHomDf_P2,
template_SxS = P1_SxS_Assigned,
modify_SxS = P2_SxS_Assigned)
## ---- eval = FALSE------------------------------------------------------------
# save(LGHomDf_P1a,LGHomDf_P2c, file = "LGHomDf_stacks.Rdata") #for example..
## ---- eval = FALSE------------------------------------------------------------
# P2_SxS_Assigned <- assign_linkage_group(linkage_df = SN_SS_P2,
# LG_hom_stack = LGHomDf_P2c, #this is changed
# SN_colname = "marker_a",
# unassigned_marker_name = "marker_b",
# phase_considered = "coupling",
# LG_number = 5,
# LOD_threshold = 3,
# ploidy = 4)
## ---- eval = FALSE------------------------------------------------------------
# marker_assignments_P1 <- homologue_lg_assignment(input_type = "probabilistic",
# probgeno_df = geno2,
# chk = chk1,
# assigned_list = list(P1_SxS_Assigned),
# assigned_markertypes = list(c(1,1)),
# LG_hom_stack = LGHomDf_P1a,
# target_parent = "P1",
# other_parent = "P2",
# ploidy = 4,
# pairing = "random",
# convert_palindrome_markers = FALSE,
# LG_number = 5,
# LOD_threshold = 3,
# write_intermediate_files = FALSE)
#
# marker_assignments_P2 <- homologue_lg_assignment(input_type = "probabilistic",
# probgeno_df = geno2,
# chk = chk1,
# assigned_list = list(P2_SxS_Assigned),
# assigned_markertypes = list(c(1,1)),
# LG_hom_stack = LGHomDf_P2c,
# target_parent = "P2",
# other_parent = "P1",
# ploidy = 4,
# pairing = "random",
# convert_palindrome_markers = FALSE,
# LG_number = 5,
# LOD_threshold = 3,
# write_intermediate_files = FALSE)
## ---- eval = FALSE------------------------------------------------------------
# marker_assignments <- check_marker_assignment(marker_assignments_P1,marker_assignments_P2)
## ---- eval = FALSE------------------------------------------------------------
# saveRDS(marker_assignments, file = "marker_assignments.RDS")
## ---- eval = FALSE------------------------------------------------------------
# all_linkages_list_P1 <- finish_linkage_analysis(input_type = "probabilistic",
# marker_assignment = marker_assignments$P1,
# probgeno_df = geno2,
# chk = chk1,
# target_parent = "P1",
# other_parent = "P2",
# convert_palindrome_markers = FALSE,
# ploidy = 4,
# pairing = "random",
# LG_number = 5,
# ncores = nc)
#
# all_linkages_list_P2 <- finish_linkage_analysis(input_type = "probabilistic",
# marker_assignment = marker_assignments$P2,
# probgeno_df = geno2,
# chk = chk1,
# target_parent = "P2",
# other_parent = "P1",
# convert_palindrome_markers = TRUE,
# ploidy = 4,
# pairing = "random",
# LG_number = 5,
# ncores = nc)
## ---- eval = FALSE------------------------------------------------------------
# linkages <- list()
# for(lg in names(all_linkages_list_P1)){
# linkages[[lg]] <- rbind(all_linkages_list_P1[[lg]], all_linkages_list_P2[[lg]])
# }
## ---- eval = FALSE------------------------------------------------------------
# saveRDS(linkages, file = "linkages.RDS")
## ---- eval = FALSE------------------------------------------------------------
# linkages <- readRDS("linkages.RDS")
## ---- eval = FALSE------------------------------------------------------------
# integrated.maplist <- MDSMap_from_list(linkages)
## ---- eval = FALSE------------------------------------------------------------
# phased.maplist <- create_phased_maplist(input_type = "probabilistic",
# maplist = integrated.maplist,
# chk = chk1,
# ploidy = 4,
# marker_assignment.1 = marker_assignments$P1,
# marker_assignment.2 = marker_assignments$P2)
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