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Last data update: 2014.03.03

R: Markov chain Monte Carlo Methods for Pedigree Reconstruction...

MCMCped

R Documentation

Markov chain Monte Carlo Methods for Pedigree Reconstruction and Analysis

Description

Markov chain Monte Carlo methods for estimating the joint posterior distribution of a pedigree and the parameters that predict its structure using genetic and non-genetic data. These parameters can be associated with covariates of fecundity such as a sexually selected trait or age, or can be associated with spatial or heritable traits that relate parents to specific offspring. Population size, allele frequencies, allelic dropout rates, and stochastic genotyping error rates can also be simultaneously estimated.

Usage

MCMCped(PdP=PdataPed(), GdP=GdataPed(), sP=startPed(), tP=tunePed(), 
   pP=priorPed(), mm.tol=999, nitt = 13000, thin = 10,  burnin = 
   3000, write_postG = FALSE, write_postA=FALSE, write_postP = 
   "MARGINAL", checkP = FALSE, jointP = TRUE, DSapprox=FALSE, verbose=TRUE)

Arguments

`PdP`	optional `PdataPed` object containing phenotypic data
`GdP`	optional `GdataPed` object containing genetic data
`sP`	optional `startPed` object containing starting parameterisation
`tP`	optional `tunePed` object containg tuning parameters for Metropolis Hastings updates
`pP`	optional `priorPed` object containg prior specifications
`mm.tol`	maximum number of mismatches tollerated
`nitt`	number of MCMC iterations
`thin`	thinning interval of the Markov chain
`burnin`	the number of initial iterations to be discarded
`write_postG`	if `TRUE` the marignal posterior distribution of true genotypes is stored
`write_postA`	if `TRUE` the joint posterior distribution of allele frequencies is stored
`write_postP`	if `"MARGINAL"` the marginal distribution of parents is stored. If `"JOINT"` the joint distribution of parents (the pedigree) is stored.
`checkP`	if `TRUE` the pedigree is checked for legality, and illegal pedigrees rejected. If `FALSE` it is assumed that any potential parent would produce a legal pedigree, i.e one without circuits, in the terminology of graph theory.
`jointP`	if `TRUE` both parents are sampled simultaneously, if `FALSE` each parent is sampled conditional on the other. `TRUE` should mix faster, but `FALSE` should iterate faster, especially when `relational="MATE"` is passed to `varPed`
`DSapprox`	if `TRUE` the likelihood for models in which a `relational="MATE"` variable is passed is approximated. This can be much more efficient because the denominator of the multinomial is the summed linear pedictors for combinations in which i=m or j=m where m referes to the "MATE" at the current iteration.
`verbose`	if `TRUE` posterior samples and the Metropolis Hastings accpetance rates of `beta`, `USdam`, `USsire`, `E1`, `E2` are printed to the screen every 1000 iterations.

Value

`beta`	an `mcmc` object containing samples from the posterior distribution of the population level parameters
`USdam`	an `mcmc` object containing samples from the posterior distribution of the number of unsampled females
`USsire`	an `mcmc` object containing samples from the posterior distribution of the number of unsampled males
`E1`	an `mcmc` object containing samples from the posterior distribution of allelic dropout rates for codominant markers or the probability of mis-scoring a dominant allele as recessive for dominant markers
`E2`	an `mcmc` object containing samples from the posterior distribution of stochasting genotyping error rates for codominant markers or the probability of mis-scoring a recessive allele as dominant for dominant markers
`G`	list of marginal distributions of true genotypes at each locus
`A`	list of `mcmc` objects containing samples from the posterior distribution of the base population allele frequencies at each locus
`P`	either samples from the posterior distribution of the pedigree, or the marginal distribution of parents

Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

References

Hadfield J.D. et al (2006) Molecular Ecology 15 3715-31

Examples


data(WarblerP)
data(WarblerG)

GdP<-GdataPed(WarblerG)

var1<-expression(varPed(c("lat", "long"), gender="Male", 
  relational="OFFSPRING"))

# paternity is to be modelled as a function of distance 
# between offspring and male territories

res1<-expression(varPed("offspring", restrict=0))

# indivdiuals from the offspring generation are excluded as parents

res2<-expression(varPed("terr", gender="Female", relational="OFFSPRING",
  restrict="=="))

# mothers not from the offspring territory are excluded
 
PdP<-PdataPed(formula=list(var1,res1,res2), data=WarblerP, USsire=FALSE)
tP<-tunePed(beta=30)

model1<-MCMCped(PdP=PdP, GdP=GdP, tP=tP, nitt=300, thin=1, burnin=0) 

plot(model1$beta)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MasterBayes)
Loading required package: coda
Loading required package: genetics
Loading required package: combinat

Attaching package: 'combinat'

The following object is masked from 'package:utils':

    combn

Loading required package: gdata
gdata: read.xls support for 'XLS' (Excel 97-2004) files ENABLED.

gdata: read.xls support for 'XLSX' (Excel 2007+) files ENABLED.

Attaching package: 'gdata'

The following object is masked from 'package:stats':

    nobs

The following object is masked from 'package:utils':

    object.size

The following object is masked from 'package:base':

    startsWith

Loading required package: gtools
Loading required package: MASS
Loading required package: mvtnorm


NOTE: THIS PACKAGE IS NOW OBSOLETE.



  The R-Genetics project has developed an set of enhanced genetics

  packages to replace 'genetics'. Please visit the project homepage

  at http://rgenetics.org for informtion.




Attaching package: 'genetics'

The following objects are masked from 'package:base':

    %in%, as.factor, order

Loading required package: kinship2
Loading required package: Matrix
Loading required package: quadprog
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MasterBayes/MCMCped.Rd_%03d_medium.png", width=480, height=480)
> ### Name: MCMCped
> ### Title: Markov chain Monte Carlo Methods for Pedigree Reconstruction and
> ###   Analysis
> ### Aliases: MCMCped
> ### Keywords: models
> 
> ### ** Examples
> 
> 
> data(WarblerP)
> data(WarblerG)
> 
> GdP<-GdataPed(WarblerG)
> 
> var1<-expression(varPed(c("lat", "long"), gender="Male", 
+   relational="OFFSPRING"))
> 
> # paternity is to be modelled as a function of distance 
> # between offspring and male territories
> 
> res1<-expression(varPed("offspring", restrict=0))
> 
> # indivdiuals from the offspring generation are excluded as parents
> 
> res2<-expression(varPed("terr", gender="Female", relational="OFFSPRING",
+   restrict="=="))
> 
> # mothers not from the offspring territory are excluded
>  
> PdP<-PdataPed(formula=list(var1,res1,res2), data=WarblerP, USsire=FALSE)
> tP<-tunePed(beta=30)
> 
> model1<-MCMCped(PdP=PdP, GdP=GdP, tP=tP, nitt=300, thin=1, burnin=0) 

 Starting parameterisation

                      beta = 
                              -0.04818

                        E1 = 
                               0.00500

                        E2 = 
                               0.00500
> 
> plot(model1$beta)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>