poppr (version 1.0.5)

poppr: Produce a basic summary table for population genetic analyses.

Description

This function allows the user to quickly view indecies of distance, heterozygosity, and inbreeding to aid in the decision of a path to further analyze a specified dataset. It natively takes genind formatted files, but can convert any raw data formats that adegenet can take (fstat, structure, genetix, and genpop) as well as genalex files exported into a csv format (see read.genalex for details).

Usage

poppr(pop, total = TRUE, sublist = c("ALL"), blacklist = c(NULL),
  sample = 0, method = 1, missing = "ignore", cutoff = 0.05,
  quiet = FALSE, clonecorrect = FALSE, hier = c(1),
  dfname = "population_hierarchy", keep = 1, hist = TRUE, minsamp = 10)

Arguments

pop

a genind object OR any fstat, structure, genetix, genpop, or genalex formatted file.

total

default TRUE. Should indecies be calculated for the combined populations represented in the entire file?

sublist

a list of character strings or integers to indicate specific population names (located in $pop.names within the genind object) Defaults to "ALL".

blacklist

a list of character strings or integers to indicate specific populations to be removed from analysis. Defaults to NULL.

sample

an integer indicating the number of permutations desired to obtain p-values. Sampling will shuffle genotypes at each locus to simulate a panmictic population using the observed genotypes. Calculating the p-value includes the observed statistics, s

method

an integer from 1 to 4 indicating the method of sampling desired. see shufflepop for details.

missing

how should missing data be treated? "zero" and "mean" will set the missing values to those documented in na.replace. "loci" and "geno" will remov

cutoff

numeric 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)

quiet

Should the function print anything to the screen while it is performing calculations? TRUE prints nothing, FALSE (defualt) will print the population name and a progress bar.

clonecorrect

default FALSE. must be used with the hier and dfname parameters, or the user will potentially get undesiered results. see clonecorrect for details.

hier

a 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 pop

dfname

a character 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.

keep

an 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

hist

logical if TRUE a histogram will be produced for each population.

minsamp

an integer indicating the minimum number of individuals to resample for rarefaction analysis.

Value

• Pop
  A vector indicating the pouplation factor
• N
  An integer vector indicating the number of individuals/isolates in the specified population.
• MLG
  An integer vector indicating the number of multilocus genotypes found in the specified poupulation, (see: mlg)
• eMLG
  The expected number of MLG at the lowest common sample size (set by the parameter minsamp.
• SE
  The standard error for the rarefaction analysis
• H
  Shannon-Weiner Diversity index
• G
  Stoddard and Taylor's Index
• Hexp
  Expected heterozygosity or Nei's 1987 genotypic diversity corrected for sample size.
• E.5
  Evenness
• Ia
  A numeric vector giving the value of the Index of Association for each population factor, (see ia).
• p.Ia
  A numeric vector indicating the p-value for Ia from the number of reshufflings indicated in sample. Lowest value is 1/n where n is the number of observed values.
• rbarD
  A numeric vector giving the value of the Standardized Index of Association for each population factor, (see ia).
• p.rD
  A numeric vector indicating the p-value for rbarD from the number of reshufflings indicated in sample. Lowest value is 1/n where n is the number of observed values.
• File
  A vector indicating the name of the original data file.

References

Paul-Michael Agapow and Austin Burt. Indices of multilocus linkage disequilibrium. Molecular Ecology Notes, 1(1-2):101-102, 2001

A.H.D. Brown, M.W. Feldman, and E. Nevo. Multilocus structure of natural populations of hordeum spontaneum. Genetics, 96(2):523-536, 1980.

Niklaus J. Gr"unwald, Stephen B. Goodwin, Michael G. Milgroom, and William E. Fry. Analysis of genotypic diversity data for populations of microorganisms. Phytopathology, 93(6):738-46, 2003

Bernhard Haubold and Richard R. Hudson. Lian 3.0: detecting linkage disequilibrium in multilocus data. Bioinformatics, 16(9):847-849, 2000.

Kenneth L.Jr. Heck, Gerald van Belle, and Daniel Simberloff. Explicit calculation of the rarefaction diversity measurement and the determination of sufficient sample size. Ecology, 56(6):pp. 1459-1461, 1975

S H Hurlbert. The nonconcept of species diversity: a critique and alternative parameters. Ecology, 52(4):577-586, 1971.

J.A. Ludwig and J.F. Reynolds. Statistical Ecology. A Primer on Methods and Computing. New York USA: John Wiley and Sons, 1988.

Masatoshi Nei. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89(3):583-590, 1978.

Jari Oksanen, F. Guillaume Blanchet, Roeland Kindt, Pierre Legendre, Peter R. Minchin, R. B. O'Hara, Gavin L. Simpson, Peter Solymos, M. Henry H. Stevens, and Helene Wagner. vegan: Community Ecology Package, 2012. R package version 2.0-5.

E.C. Pielou. Ecological Diversity. Wiley, 1975.

Claude Elwood Shannon. A mathematical theory of communication. Bell Systems Technical Journal, 27:379-423,623-656, 1948

J M Smith, N H Smith, M O'Rourke, and B G Spratt. How clonal are bacteria? Proceedings of the National Academy of Sciences, 90(10):4384-4388, 1993.

J.A. Stoddart and J.F. Taylor. Genotypic diversity: estimation and prediction in samples. Genetics, 118(4):705-11, 1988.

See Also

clonecorrect, poppr.all, ia, missingno, mlg

Examples

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")