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## Bootstrap of NJ tree of populations. As input takes bootstraped tree, source data in geneind format and number of permutations. | ||
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boot.phylo.nj.pop <- function(origtree, genindata, nperm) { | ||
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# Custom variant of function sample to correct its behaviour when number of individuals within respective population is 1. | ||
mysample <- function(x){ | ||
if (length(x) == 1) {out <- x} | ||
else {out <- sample(x, replace=TRUE)} | ||
return(out) | ||
} | ||
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# Construction of NJ tree from bootstraped dataset for further comparison with original tree. | ||
## Here it is possible to adjust type and/or parameters of distance matrix and/or tree constructioning. | ||
treemaker <- function (ind, listgenpopobj) { | ||
OpravaMatice <- dist.genpop(listgenpopobj[[ind]], method=1, diag=TRUE, upper=TRUE) | ||
OpravaMatice[OpravaMatice == "Inf"] <- 10 | ||
nj(OpravaMatice) | ||
} | ||
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# Extraction of needed information from orginal data and preparation of temporal variables. | ||
genindata2 <- genindata | ||
data <- genindata@tab | ||
pop <- genindata@pop | ||
indiv <- 1:nrow(genindata@tab) | ||
res <- vector(mode="list", length=nperm) | ||
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# In every step (from 1 to number of permutations) sample within respective populations of source data and write it into list of geneind objects. | ||
for (index in 1:nperm) { | ||
struct <- unlist(tapply(indiv, pop, mysample)) | ||
new.tab <- data[struct,] | ||
genindata2@tab <- new.tab | ||
# For correct writing of modified data to the list. | ||
res[[index]] <- genindata2 | ||
} | ||
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# Conversion of all genind objects in the list to genpop objects. | ||
population <- lapply(res, genind2genpop) | ||
# Construction of trees and saving of them into the list of trees. | ||
trees <- vector("list", nperm) | ||
trees <- lapply(1:nperm, treemaker, population) | ||
# Compare every bootstraped tree with original one and return vector of bootstrap support values. | ||
for (i in 1:nperm) storage.mode(trees[[i]]$Nnode) <- "integer" | ||
storage.mode(origtree$Nnode) <- "integer" | ||
pp <- prop.part(trees) | ||
pp <- postprocess.prop.part(pp) | ||
ans <- prop.clades(origtree, part=pp, rooted=FALSE) | ||
return(ans) | ||
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} |
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H39 Sk 339/341 198/180 211/211 397/399 191/209 194/194 251/251 165/187 219/221 132/138 279/279 150/152 | ||
H40 Sk 273/273 198/198 221/223 401/401 187/187 168/192 245/249 191/191 213/221 126/134 279/287 150/152 | ||
H41 Sk 325/341 198/198 211/221 399/409 197/197 168/192 261/261 181/185 219/219 130/136 277/303 152/152 | ||
H42 Sk 341/343 198/198 221/221 401/409 NA 192/192 245/251 187/191 219/221 130/132 275/277 150/156 | ||
H43 Sk 341/343 198/198 221/221 399/409 NA 192/192 245/251 187/191 219/221 130/132 275/277 150/156 | ||
H44 Sk 275/283 198/198 221/223 415/419 197/197 198/198 237/251 165/183 211/219 114/130 283/293 150/150 | ||
H45 Sk 283/283 198/180 221/221 403/419 NA 168/168 237/251 165/165 211/211 128/132 279/283 152/152 | ||
H46 Sk 275/275 198/198 221/221 419/419 193/193 168/196 243/251 165/165 215/215 128/136 277/293 150/152 | ||
H47 Sk 275/275 198/198 221/221 419/419 193/193 168/196 243/251 165/165 215/215 128/136 277/293 150/152 |
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