psex_Fis compute the probability that repeated
genotypes originate from distinct sexual events (i.e. being different genets
and not ramets of the same MLG), with or without taking account of H-W equilibrium departures.
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option, the method of psex calculation (see details).
option, numeric, the population is simulated
We strongly recommand to use
RR = TRUE option to compute allelic
frequencies for clonal data.
Otherwise, we let the options to work with frequencies at genet level
genet = TRUE) or ramet level (
RR = FALSE and
genet = FALSE).
MLGsim = TRUE,
psex are computed as probability for two
units to be derived from distinct sexual reproductive event to be
(Stenberg et al. 2003).
MLGsim = FALSE,
psex are computed with more conservative
C(n,1) (Parks & Werth 1993) with
n, "number of separated
fragments with identical genotype to some previously encountered ramet".
The pvalue method calculation is largely inspired from MLGsim (Stenberg et al., 2003)
and MLGsim2.0 (Ivens et al., 2012), with authors agreements.
For each repeat, a population is simulated with allelic frequencies.
If clones occurred, a simulated
psex is computed and kept in memory.
At the end, a distribution of
sim psex is constructed and p-value is
computed as upper p-value (Monte Carlo).
psex_Fis could be time consuming with a certain
number of repeats.
Values must differ from MLGsim and MLGsim2.0 because of Round-Robin frequencies
Fis calculation (see
For one population:
nbrepeat is not provided, a table with psex values,
nbrepeat is provided, a list of a table with
and p-values and a vector of
data1 is a multi-population table (
vecpop != NULL),
a list of either tables/tables and vectors for each population.
sim_psex are less than 100, a warning message pops, as
clones are not necessarily generated each simulation.
If no repeated genotype is generated during simulations, a warning message pops as well.
The R implementation of
RClone was written by Diane Bailleul.
The design was inspired by GenClone program described in Arnaud-Haond & Belkhir (2007).
Stenberg et al., 2003, MLGsim: a program for detecting clones using a simulation approach.
Arnaud-Haond et al., 2007, Standardizing methods to address clonality in population studies.
Ivens, A.B.F., van de Sanden, M. and Bakker, J. MLGsim 2.0: updated software for
detecting clones from micro satellite data using a simulation approach.
In: The Evolutionary Ecology of Mutualism. PhD Thesis, 2012, University of Groningen. Pg 107-111
http://www.rug.nl/research/institute-evolutionary-life-sciences/tres/downloads for MLGsim 2.0.
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