if genclone = FALSE{ The resulting genind object
will have a data frame in the other slot called
population_hierarchy. This will contain a column for your population
data and a column for your Regional data if you have set the flag.} if genclone = TRUE{ The resulting genclone object will
have a single hierarchical level defined in the hierarchy slot. This will
be called "Pop" and will reflect the population factor defined in the
genalex input. If region = TRUE, a second column will be inserted
and labeled "Region". If you have more than two hierarchical levels within
your data set, you should run the command splithierarchy on
your data set to define the unique hierarchical levels. }
FOR POLYPLOID (> 2n) DATA SETS{ Adegenet's genind object has
an all-or-none approach to missing data. If a sample has missing data at a
particular locus, then the entire locus is considered missing. This works
for diploids and haploids where allelic dosage is unambiguous. For
polyploids this poses a problem as much of the data set would be
transformed into missing data. With this function, I have created a
workaround.
When importing polyploid data sets, missing data is scored as "0" and kept
within the genind object as an extra allele. This will break most analyses
relying on allele frequencies*. All of the functions in poppr will work
properly with these data sets as multilocus genotype analysis is agnostic
of ploidy and we have written both Bruvo's distance and the index of
association in such a way as to be able to handle polyploids presented in
this manner.
* To restore functionality of analyses relying on allele frequencies, use
the recode_polyploids function.}