## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 4, 
  fig.height= 4,
  eval = FALSE
)
options(rmarkdown.html_vignette.check_title = FALSE)

## ----load_data----------------------------------------------------------------
# library(mappoly)
# file.name <- system.file("extdata/potato_example.csv", package = "mappoly")
# dat <- read_geno_csv(file.in = file.name, ploidy = 4)
# print(dat, detailed = T)
# plot(dat)

## ----eval=FALSE, filter_ind_donot_eval----------------------------------------
# dat <- filter_individuals(dat)

## ----filter-------------------------------------------------------------------
# dat <- filter_missing(dat, type = "marker", filter.thres = .05)
# dat <- filter_missing(dat, type = "individual", filter.thres = .05)

## ----filter_seg---------------------------------------------------------------
# seq.filt <- filter_segregation(dat, chisq.pval.thres = 0.05/dat$n.mrk)
# seq.filt <- make_seq_mappoly(seq.filt)
# seq.red  <- elim_redundant(seq.filt)

## ----make_seq-----------------------------------------------------------------
# seq.init <- make_seq_mappoly(seq.red)
# plot(seq.init)

## ----geno_ord-----------------------------------------------------------------
# go <- get_genomic_order(input.seq = seq.init) ## get genomic order of the sequence
# plot(go)

## ----twopt_show, eval=FALSE---------------------------------------------------
# ncores <- parallel::detectCores() - 1
# tpt <- est_pairwise_rf2(seq.init, ncpus = ncores)
# m <- rf_list_to_matrix(tpt) ## converts rec. frac. list into a matrix
# sgo <- make_seq_mappoly(go) ## creates a sequence of markers in the genome order
# plot(m, ord = sgo, fact = 5) ## plots a rec. frac. matrix using the genome order, averaging neighbor cells in a 5 x 5 grid

## ----group--------------------------------------------------------------------
# g <- group_mappoly(m, expected.groups = 12, comp.mat = TRUE)
# plot(g)
# g

## ----select_group-------------------------------------------------------------
# s1 <- make_seq_mappoly(g, 1, ## Select LG1
#                        genomic.info = 1)
# m1 <- make_mat_mappoly(m, s1)

## ----order_mds----------------------------------------------------------------
# mds.o1 <- mds_mappoly(input.mat = m1)
# s1.mds <- make_seq_mappoly(mds.o1)
# plot(m1, ord = s1.mds)

## ----order_genome-------------------------------------------------------------
# gen.o1 <- get_genomic_order(s1)
# s1.gen <- make_seq_mappoly(gen.o1)
# plot(m1, ord = s1.gen)

## ----map_lg1, results = FALSE, eval = FALSE-----------------------------------
# tpt1 <- est_pairwise_rf(s1.mds, ncpus = ncores)
# lg1.map <- est_rf_hmm_sequential(input.seq = s1.mds,
#                                 start.set = 3,
#                                 thres.twopt = 10,
#                                 thres.hmm = 20,
#                                 extend.tail = 50,
#                                 info.tail = TRUE,
#                                 twopt = tpt1,
#                                 sub.map.size.diff.limit = 5,
#                                 phase.number.limit = 20,
#                                 reestimate.single.ph.configuration = TRUE,
#                                 tol = 10e-3,
#                                 tol.final = 10e-4)

## ----map_lg1_plot-------------------------------------------------------------
# print(lg1.map)
# plot(lg1.map, mrk.names = TRUE, cex = 0.7)

## ----map_err_lg1, results='hide'----------------------------------------------
# lg1.map.up <- est_full_hmm_with_global_error(input.map = lg1.map, error = 0.05,
#                                              verbose = TRUE)
# plot(lg1.map.up, mrk.names = TRUE, cex = 0.7)

## ----map_reest, results='hide'------------------------------------------------
# lg1.map.ols <- reest_rf(lg1.map, m1, method = "ols")
# lg1.map.mds <- reest_rf(lg1.map, m1, method = "wMDS_to_1D_pc", input.mds = mds.o1)

## ----map_list,  results='hide'------------------------------------------------
# map.list.lg1  <- list(orig = lg1.map,
#                       updt = lg1.map.up,
#                       ols = lg1.map.ols,
#                       mds = lg1.map.mds)
# plot_map_list(map.list.lg1, col = "ggstyle", title = "Estimation method")

## ----homolog_p----------------------------------------------------------------
# g1 <- calc_genoprob_error(lg1.map.up, step = 1, error = 0.05)
# to.qtlpoly <- export_qtlpoly(g1) #export to QTLpoly
# h1 <- calc_homologprob(g1)
# plot(h1, lg = 1, ind = 10)

## ----meiosis_evaluation-------------------------------------------------------
# p1 = calc_prefpair_profiles(g1)
# plot(p1, min.y.prof = 0.25, max.y.prof = 0.4, P1 = "Atlantic", P2 = "B1829.5")

## ----eval=FALSE---------------------------------------------------------------
# export_map_list(lg1.map.up, file = "output_file.csv")

## -----------------------------------------------------------------------------
# in.file <- "https://github.com/mmollina/SCRI/raw/main/docs/tetra/maps_updated.rda"
# map_file <- tempfile()
# download.file(in.file, map_file)
# load(map_file)

## -----------------------------------------------------------------------------
# plot_genome_vs_map(MAPs.up, same.ch.lg = TRUE)

## -----------------------------------------------------------------------------
# summary_maps(MAPs.up)