| group_upgma | R Documentation | 
Identifies linkage groups of markers using the results of two-point (pairwise) analysis and UPGMA method. Function adapted from MAPpoly package written by Marcelo Mollinari.
group_upgma(input.seq, expected.groups = NULL, inter = TRUE, comp.mat = FALSE)
| input.seq | 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  | 
Returns an object of class 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  | 
| LOD | minimum LOD Score to declare linkage. | 
| max.rf | maximum recombination fraction to declare linkage. | 
| twopt | name of the object of class  | 
Marcelo Mollinari, mmollin@ncsu.edu
Cristiane Taniguti chtaniguti@tamu.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")}
 data("vcf_example_out")
 twopts <- rf_2pts(vcf_example_out)
 input.seq <- make_seq(twopts, "all")
 lgs <- group_upgma(input.seq, expected.groups = 3, comp.mat=TRUE, inter = FALSE)
 plot(lgs)
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