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Ht <- function(Table){
#Variables
#------------------------------------------------------------------------------------------------------------------------------
# Input:
# Table <- Dest.calc(), Gst.est.calc();
#------------------------------------------------------------------------------------------------------------------------------
# function to calculate the total heterozygosity.
# The argument 'Table' has to be of the following format:
# allele number population locus proportion
# 4 1 Borkum LoPi89 0.1250000
# 5 1 Borkum LoPi89 0.1250000
# 6 2 Borkum LoPi89 0.2500000
# 7 0 Borkum LoPi89 0.0000000
# 8 3 Borkum LoPi89 0.3750000
# 9 1 Borkum LoPi89 0.1250000
# 4 1 Langeoog LoPi89 0.1666667
# 5 1 Langeoog LoPi89 0.1666667
# 6 1 Langeoog LoPi89 0.1666667
# 7 2 Langeoog LoPi89 0.3333333
# 8 1 Langeoog LoPi89 0.1666667
# 9 0 Langeoog LoPi89 0.0000000
# 4 0 Wangerooge LoPi89 0.0000000
# 5 1 Wangerooge LoPi89 0.1250000
# 6 0 Wangerooge LoPi89 0.0000000
# 7 4 Wangerooge LoPi89 0.5000000
# 8 2 Wangerooge LoPi89 0.2500000
# 9 1 Wangerooge LoPi89 0.1250000
Table2 <- split(Table,Table$locus)
Ht.one.locus <- lapply(Table2,Ht.value.calculations)
Ht.values1 <- do.call(rbind,Ht.one.locus)
Ht.values <- cbind(Ht.values1,names(Table2))
# The Ht values for the several loci are combined with a column that
# contains the names of the loci, the Ht-value belongs to.
Ht.values <- as.data.frame(Ht.values)
colnames(Ht.values) <- c("Ht.value","locus")
invisible(Ht.values)
}
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