run_mcmc: Run the MCMC for full sibling inference

Description Usage Arguments Examples

Description

Run the MCMC for full sibling inference

Usage

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run_mcmc(genos, mu = 0.005, pair_prob_cutoff = 0.001, burn_in, num_sweeps)

Arguments

burn_in

Number of sweeps to discard as burn-in. (In one sweep, every individual in the sample has been updated once by Gibbs sampling.)

num_sweeps

Number of sweeps after burn in to use as a sample for MCMC.

genos

The data frame of SNP genotypes

mu

Genotyping error rates per locus (recycles as necessary)

pair_prob_cutoff

the fraction of simulated full sib pairs that should have a log-likelihood ratio for the sibling relationship less than the cutoff that will be used. (The value pair_prob_cutoff is used to determine the which pairs have a high enough log-likelihood ratio to be considered as possible full siblings.)

Examples

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# this is a much shorter run than one should do:
run_mcmc(fs_dev_test_data$chinook_full_sibs_genos, burn_in = 3, num_sweeps = 5)

eriqande/fullsniplings documentation built on May 16, 2019, 8:45 a.m.