[R] genotypes simulation

Claire_6700 chriseverclear at hotmail.com
Tue May 6 01:25:43 CEST 2008


thank you. i will take a look

claire,

Neil Shephard wrote:
> 
> 
> 
> Claire_6700 wrote:
>> 
>> Hello,
>> 
>> I am having really hard time finding a good article about simulating
>> genotypes of cases and controls at a disease locus using R.
>> 
>> if you guys can point me or guide me where i can find more information,
>> it will be helpful.
>> 
>> 
> 
> The popgen() package allows the simulation of genotype data under a
> coalescent model (via the treesim() function) or Multinomial-Drichlet
> model (via the simMD() function).  These won't quite simulate case-control
> data, but can no doubt be tweaked to get two sets of data (cases and
> controls) with the desired allele frequencies, LD etc.
> 
> There is also the rmetasim() package which interfaces R with metasim.
> 
> Alternatively if your after validation of p-values derived from genotypic
> tests of association via simulation there is also the Direction Simulation
> Approach (DSA) which is implemented in R
> (http://www.mpipsykl.mpg.de/pages/english/research/mueller_downloads.htm).
> 
> There is also an R plugin for plink
> (http://pngu.mgh.harvard.edu/~purcell/plink/) which performs simulation of
> unlinked loci that are in linkage equilibrium (although you may
> specifically want to model linkage disequilibrium).
> 
> And there is an R-plugin for PBAT which is for Population Based
> Association Tests (http://people.fas.harvard.edu/~tjhoffm/pbatR.html).
> 
> For other R-genetics information you may find the task-view at
> http://cran.r-project.org/web/views/Genetics.html useful as well as
> http://rgenetics.org/
> 
> There are also a host of other non-R options available though.  Many under
> the coalescent model (including one of the first by Richard Hudson, the ms
> program) are linked from
> http://en.wikipedia.org/wiki/Coalescent_theory#Software and additional
> software for genetic analysis (including simulation in some instances)  at
> http://linkage.rockefeller.edu/soft/ .  The vast majority will simply dump
> output to text files, so its straight-forward to call them from within R
> via a system call and then read the results into R.
> 
> Neil
> 

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