group_mappoly | R Documentation |
Identifies linkage groups of markers using the results of two-point (pairwise) analysis.
group_mappoly(
input.mat,
expected.groups = NULL,
inter = TRUE,
comp.mat = FALSE,
LODweight = FALSE,
verbose = TRUE
)
input.mat |
an object of class |
expected.groups |
when available, inform the number of expected linkage groups (i.e. chromosomes) for the species |
inter |
if |
comp.mat |
if |
LODweight |
if |
verbose |
logical. If |
Returns an object of class mappoly.group
, which is a list
containing the following components:
data.name |
the referred dataset name |
hc.snp |
a list containing information related to the UPGMA grouping method |
expected.groups |
the number of expected linkage groups |
groups.snp |
the groups to which each of the markers belong |
seq.vs.grouped.snp |
comparison between the genomic group information
(when available) and the groups provided by |
chisq.pval.thres |
the threshold used on the segregation test when reading the dataset |
chisq.pval |
the p-values associated with the segregation test for all markers in the sequence |
Marcelo Mollinari, mmollin@ncsu.edu
Mollinari, M., and Garcia, A. A. F. (2019) Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models, _G3: Genes, Genomes, Genetics_. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1534/g3.119.400378")}
## Getting first 20 markers from two linkage groups
all.mrk <- make_seq_mappoly(hexafake, c(1:20,601:620))
red.mrk <- elim_redundant(all.mrk)
unique.mrks <- make_seq_mappoly(red.mrk)
counts <- cache_counts_twopt(unique.mrks, cached = TRUE)
all.pairs <- est_pairwise_rf(input.seq = unique.mrks,
count.cache = counts,
ncpus = 1,
verbose = TRUE)
## Full recombination fraction matrix
mat.full <- rf_list_to_matrix(input.twopt = all.pairs)
plot(mat.full, index = FALSE)
lgs <- group_mappoly(input.mat = mat.full,
expected.groups = 2,
inter = TRUE,
comp.mat = TRUE, #this data has physical information
verbose = TRUE)
lgs
plot(lgs)
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