genind
formatted
files, but can convert any raw data formats that adegenet
can take (fstat, structure, gentix, and genpop) as well
as genalex files exported into a csv format (see
read.genalex
for details).poppr(pop, total = TRUE, sublist = c("ALL"),
blacklist = c(NULL), sample = 0, method = 1,
missing = "ignore", cutoff = 0.05, quiet = "minimal",
clonecorrect = FALSE, hier = c(1),
dfname = "population_hierarchy", keep = 1, hist = TRUE,
minsamp = 10)
genind
object OR any fstat,
structure, gentix, genpop, or genalex formatted file.TRUE
. Should indecies be
calculated for the combined populations represented in
the entire file?$pop.names
within the genind
object)
Defaults to "ALL".popsample
for
details."zero"
and "mean"
will set the missing
values to those documented in na.replace
.
"loci"
and "geno"
will removnumeric
a number from 0 to 1
indicating the percent missing data allowed for analysis.
This is to be used in conjunction with the flag
missing
(see missingno
for details)TRUE
prints nothing, "minimal"
(defualt) will print the
population name and dots indicating permutation progress,
FALSE
wiFALSE
. must be used
with the hier
and dfname
parameters, or the
user will potentially get undesiered results. see
clonecorrect
for details.numeric or character list
. This is
the list of vectors within a data frame (specified in
dfname
) in the 'other' slot of the
genind
object. The list should indicate the
popcharacter string
. This is the name
of the data frame or list containing the vectors of the
population hierarchy within the other
slot of the
genind
object.integer
. This indicates the levels
of the population hierarchy you wish to keep after clone
correcting your data sets. To combine the hierarchy, just
set keep from 1 to the length of your hierarchy. see
logical
if TRUE
a histogram
will be produced for each population.integer
indicating the minimum
number of individuals to resample for rarefaction
analysis.mlg
)minsamp
.ia
).sample
. Lowest value is
1/n where n is the number of observed values.ia
).sample
. Lowest value
is 1/n where n is the number of observed values.clonecorrect
, poppr.all
,
ia
, missingno
,
mlg
data(nancycats)
poppr(nancycats)
poppr(nancycats, sample=99, total=FALSE, quiet=FALSE)
# Note: this is a larger data set that could take a couple of minutes to run
# on slower computers.
data(H3N2)
poppr(H3N2, total=FALSE, sublist=c("Austria", "China", "USA"),
clonecorrect=TRUE, hier="country", dfname="x")
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