Nothing
p.value.correcture <- function(Dv.pairwise){
#Variables
#------------------------------------------------------------------------------------------------------------------------------
# Input:
# empirical.value,bootstrapped.values <- pair.pops.Gst(), pair.pops.Dest.Chao(), pair.pops.Dest();
# Output:
# Dv.pairwise.adjusted -> Workspace;
#------------------------------------------------------------------------------------------------------------------------------
# Function, that adjusts the p-values obtained for the values of genetic differentiation
# when the populations were compared pairwise.
# The argument of the function is a list that equals the result from
# the functions pair.pops.Dest(), pair.pops.Dest(Chao) and pair.pops.Gst.
# Example from pair.pops.Dest():
# $Dest.loci.pairwise.comparison
# Dest.for.locus locus population1 population2 populationpair 0.90.confidence.level 0.95.confidence.level 0.99.confidence.level p.values
# 1 0.02380959 L12 Borkum Langeoog BorkumLangeoog 0.397058823529413 0.581632653061224 0.811968774427113 0.377
# 2 0.02380959 LgleichL12 Borkum Langeoog BorkumLangeoog 0.435039370078737 0.568645833333334 0.882908352849339 0.3679
# 3 -0.37980780 LoPi89 Borkum Langeoog BorkumLangeoog 0.445945945945951 0.570634420813546 0.795169266055046 0.76
# 4 -1.62345483 ZuPop56 Borkum Langeoog BorkumLangeoog 0.457676703930741 0.58603896103893 0.811968833045222 0.98999
# 5 -0.38055556 L12 Borkum Wangerooge BorkumWangerooge 0.366245107632092 0.494946666036428 0.720114393549218 0.86
# 6 -0.38055556 LgleichL12 Borkum Wangerooge BorkumWangerooge 0.377626994315056 0.489318402011915 0.697002091010118 0.87
# 7 0.36363636 LoPi89 Borkum Wangerooge BorkumWangerooge 0.375735294117647 0.5 0.691348039215686 0.108
# 8 0.05092607 ZuPop56 Borkum Wangerooge BorkumWangerooge 0.5 0.62518115942029 0.860641307155773 0.365
# 9 -0.40833324 L12 Langeoog Wangerooge LangeoogWangerooge 0.353817629784486 0.511339285714285 0.753258482168656 0.877
# 10 -0.40833324 LgleichL12 Langeoog Wangerooge LangeoogWangerooge 0.38461300309598 0.513626104647465 0.734965986394557 0.872
# 11 -0.42721505 LoPi89 Langeoog Wangerooge LangeoogWangerooge 0.352728781412997 0.511904761904764 0.83483064516129 0.9009
# 12 -0.09848485 ZuPop56 Langeoog Wangerooge LangeoogWangerooge 0.312668918918919 0.458360777014127 0.732727077773542 0.588
#
# $Dest.mean.pairwise.comparison
# Mean.Dest population1 population2 populationpair 0.90.confidence.level 0.95.confidence.level 0.99.confidence.level p.values
# 1 -0.48891086317704 Borkum Langeoog BorkumLangeoog 0.173210036584964 0.243220947634115 0.417173218728602 0.9622
# 2 -0.0866371684787738 Borkum Wangerooge BorkumWangerooge 0.167947625574689 0.224381882908422 0.338647995015044 0.565
# 3 -0.335591596175755 Langeoog Wangerooge LangeoogWangerooge 0.136355453244588 0.211930415868027 0.339991808971277 0.9544
# A Bonferroni, Holm, Hommel and (Benjamini and Hochberg) correction of the p-values per locus
# is calculated because of the multiple comparison from one data set.
# Only the p-values referring to the same locus are adjusted at once (to
# one another).
# The p-values of the mean values of genetic differentiation measurements
# (over all loci) for the several population pairs are adjusted in the same way.
Dv.locis.correction <- split(Dv.pairwise[[1]],Dv.pairwise[[1]]$locus)
# The table is splitted according to the locis that have been
# examined.
Dv.locis.corrected1 <- lapply(Dv.locis.correction,Dv.locis.corrected.calc)
Dv.locis.corrected <- do.call(rbind,Dv.locis.corrected1)
Dv.locis.corrected <- as.data.frame(Dv.locis.corrected)
# Now the correction is carried out for the p-values that were
# calculated for the measures of genetic distance over all loci (the mean values).
p=as.numeric(as.vector(Dv.pairwise[[2]]$p.values))
p.bonferroni <- p.adjust(p,method="bonferroni")
p.holm <- p.adjust(p,method="holm")
p.hommel <- p.adjust(p,method="hommel")
pBH <- p.adjust(p,method="BH")
Dv.means.corrected <- cbind(as.data.frame(as.matrix(Dv.pairwise[[2]])),p.bonferroni,p.holm,p.hommel,pBH)
Dv.means.corrected <- as.data.frame(Dv.means.corrected)
Dv.pairwise.adjusted=list(Dv.locis.corrected,Dv.means.corrected)
assign("Dv.pairwise.adjusted",Dv.pairwise.adjusted,pos = DEMEtics.env)
}
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