genind and then creates a report containing the results of the
analysis. There are several routines that can be optionally included in the
analysis and there are multiple output options including a PDF with the
report, R-code and an object (fname.results) containing all of the
results, which can be used for further analyses.genind. There are
several ways to convert data into a genind object using
existing functions provided by the adegenet package (
import2genind,
df2genind,read.fstat,
read.structure, read.genetix
,read.genepop) or refer to read.genetable how to import
data from an EXCEL (csv) document. The function performs a number of
different genetic analyses (e.g. counts of indivuals and alleles across
sub-populations, tests for heterozygosity and Hardy-Weinberg Equilibrium,
differentiation statistics Fst, G'st, Jost's D, and genetic distance between
individuals and populations), with users having the option to select which
analysis routines are included in the report. To select a routine, the user
simply turns on a switch e.g. mk.map=TRUE returns a map with the sampling
location for each individual (if coordinates are provided). Coordinates
need to specified within the genind object. As a standard genind object does
not require spatial coordinates, we extended it by using the other
slot in the genind object. The easiest way to provide spatial coordinates is
to use the read.genetable function and use the lat, long or
x, y arguments for WGS1984 projected data or mercator
projected data respectively. To calculate distances the data are internally
reprojected using the Mercator function in package
dismo), which is the projection used by google maps. Or you
can add data manually to your genind object using the mentioned (e.g.
genindobject@other$latlong <- yourlatlong data or
genindobject@other$xy <- your_xy_data). If you have your data in a
different projection you need to reproject them into either WGS1984 or the
google maps Mercator projection. If you use a different projection distance
calculation may be wrong and probably the map will not be correct. See the
manual for an example how to project and add spatial coordinates to your
genetic data. Names for alleles (genindobject@loc.names) are
truncated if longer than six characters. If truncated Captial letters linked
by a hyphen are added to guarentee they are unique. You can rename them by
providing new names by accessing the genind@loc.names slot prior to
running popgenreport. Note that the popgenreport function can take
a long time to run if the options mk.complete, mk.gd.kosman, or mk.gd.smouse
are set to TRUE. For example, running popgenreport with
mk.complete=TRUE on a dataset with 500 individuals with 36 loci will
take 14 to 15 minutes on a PC with a 3.5 Ghz processor and nearly 3 hours
for a dataset with ~3200 individuals.
popgenreport(cats = NULL, mk.counts = TRUE, mk.map = FALSE, maptype = "satellite", mapdotcolor = "blue", mapdotsize = 1, mapdotalpha = 0.4, mapdottype = 19, mapzoom = NULL, mk.locihz = FALSE, mk.hwe = FALSE, mk.fst = FALSE, mk.gd.smouse = FALSE, mk.gd.kosman = FALSE, mk.pcoa = FALSE, mk.spautocor = FALSE, mk.allele.dist = FALSE, mk.null.all = FALSE, mk.allel.rich = FALSE, mk.differ.stats = FALSE, mk.custom = FALSE, fname = "PopGenReport", foldername = "results", path.pgr = NULL, mk.Rcode = FALSE, mk.complete = FALSE, mk.pdf = TRUE)genind object the analysis will be
based on.read.genetable on how to import them from a table of genetic data).
An error message will be generated if you turn this routine on, but do not
provide the coordinates in the right format. If the coordinates are provided
in a seperate file, they must be attached to the genind object in the slot
yourgenindobject@other$latlong <- yourlatlongdata.
yourlatlongdata needs to be a data frame that has the same number and
order of individuals per row as the population genetic data. Note that an
internet connection is required to connect to the Google Maps server which
provides the basemap for this routine.par. Default is 19 - a filled circle.gd_smouse. Spatial coordinates need to
be provided to be able to run this analysis.gd_kosman. Spatial coordinates need to be
provided to be able to run this analysis.adegenet.spautocor for more information.tempdir()). If you want to store the output in
another directory, simply provide the path here. e.g.
path.pgr=getwd() saves it in your current working directory.TRUE, except mk.subgroups).knitr package and its manuals.str(res). The main slots in this object (if you ran a
full report) are: dataoverview, PopHet, Alleledist, Fst,
HsHtdifferentiate, HWEresults, subgroups, GDKosman, GDSmouseAdditional ouput is provided in the form of a PDF (if mk.pdf=TRUE),which
will be saved to the specified subfolder (via foldername) in your current
working directory, and maps and figures which will be placed in this folder
as well. This folder will be generated automatically in your current working
directory. If you do not specify a working directory via path.pgr
then the temporary working directory of R will be used (tempdir()).
If mk.Rcode=T is set, an R file named fname.R will be saved to your
specified subfolder.
Peakall R., Smouse P. 2012. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research - an update. Bioinformatics 28:2537-2539
adegenet, pegas, mmod
#not run:
#data(bilby) # a generated data set
#res <- popgenreport(bilby, mk.counts=TRUE, mk.map=TRUE, mk.pdf=FALSE)
#check results via res or use created tables in the results folder.
### RUN ONLY with a working Latex version installed
# res <- popgenreport(bilby, mk.counts=TRUE, mk.map=TRUE, mk.pdf=TRUE, path.pgr="c:/temp")
# for a full report in a single pdf set mk.complete to TRUE
# res <- popgenreport(bilby, mk.complete=TRUE)
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