bevimed_m {BeviMed} | R Documentation |

Sample from posterior distribution of parameters under model gamma = 1 and conditional on mode of inheritance, set via the `min_ac`

argument.

```
bevimed_m(
y,
G,
min_ac = 1L,
tau_shape = c(1, 1),
pi_shape = c(6, 1),
omega_shape = if (max(min_ac) == 1L) c(2, 8) else c(2, 2),
samples_per_chain = 1000,
stop_early = FALSE,
blocks = 5,
burn = as.integer(samples_per_chain/10),
temperatures = (0:6/6)^2,
tune_temps = 0,
return_z_trace = TRUE,
return_x_trace = TRUE,
raw_only = FALSE,
swaps = as.integer(length(temperatures)/2),
optimise_z0 = FALSE,
tune_omega_and_phi_proposal_sd = FALSE,
tune_block_size = 100,
variant_weights = NULL,
standardise_weights = TRUE,
log_phi_mean = -0.15,
log_phi_sd = sqrt(0.3),
tandem_variant_updates = if (max(min_ac) == 1) 0 else min(sum(y), ncol(G)),
...
)
```

`y` |
Logical vector of case ( |

`G` |
Integer matrix of variant counts per individual, one row per individual and one column per variant. |

`min_ac` |
Integer vector with a length equalling the number of individuals or length |

`tau_shape` |
Beta shape hyper-priors for prior on rate of affection (i.e. being a case) amongst individuals with non-pathogenic variant combinations (i.e. they have less than |

`pi_shape` |
Beta shape hyper-priors for prior on rate of affection (i.e. being a case) amongst individuals with pathogenic variant combinations (i.e. they have at least |

`omega_shape` |
Beta shape hyper-priors for prior on rate of pathogenicity amongst variants. |

`samples_per_chain` |
Number of samples to draw from each chain. |

`stop_early` |
Logical value determining whether to attempt to stop the sampling as soon as certain conditions are met (i.e. either the estimated marginal log likelihood lies within a certain confidence interval, or we are sufficiently confidence that the log Bayes factor against of model gamma = 1 over model gamma = 0 is sufficiently low). |

`blocks` |
Maximum number of blocks of |

`burn` |
Number of samples to drop from the start of the chain. |

`temperatures` |
Numeric vector of temperatures of power posteriors. One chain will be created for each element of the vector at the corresponding temperature. |

`tune_temps` |
Integer value - if greater than 0, the |

`return_z_trace` |
Logical value determining whether to store the z-vectors for each chain, which uses alot of memory, particularly if |

`return_x_trace` |
Logical value determining whether to store the x variable determined by success samples of z. Potentially uses alot of memory, particularly if |

`raw_only` |
Logical value determining whether to return raw output of MCMC routine only. |

`swaps` |
Number of swaps between adjacent tempered chains to perform per update cycle. |

`optimise_z0` |
Logical value determining whether to use a simulated annealing optimisation run to tune the initial values of |

`tune_omega_and_phi_proposal_sd` |
Logical value determining whether the proposal SDs of the Metropolis-Hastings estimated parameters should be tuned for a target acceptance range. |

`tune_block_size` |
Integer value giving number of samples to draw when estimatating the acceptance rate of the omega/phi proposals. |

`variant_weights` |
Vector of log-odds off-sets for rates of pathogenicity of individual variants relative to the global rate, omega. |

`standardise_weights` |
Boolean value determining whether weights should be standardised by subtracting their mean and dividing by their sample standard deviation. If |

`log_phi_mean` |
Mean for normal prior on scaling factor phi. |

`log_phi_sd` |
SD for normal prior on scaling factor phi. Setting to 0 causes the weights to be fixed and not estimated. |

`tandem_variant_updates` |
Number of tandem variant updates to make per update cycle. |

`...` |
Other arguments to be passed to |

A `BeviMed_m`

object is a list containing elements:

‘parameters’: a list containing arguments used in the function call, including the adjusted weights used in the inference in the ‘c_weights’ slot,

‘traces’: a list of traces of model parameters from all MCMC chains for each parameter. Parameters sampled are z, omega, phi and x (the indicator of having a pathogenic configuration of alleles). The list of traces is named by parameter name, and each is a matrix where the rows correspond to samples. $z has k columns for each temperature, with the samples from the true posterior (i.e. with temperature equal to 1) of z corresponding to the final k columns. Likewise, the true posterior is given by the final column for the traces of phi and omega. The trace of x is only given for temperature equal to 1 to reduce memory usage.

‘final’: a list named by model parameter giving the final sample of each,

‘swaps’: a list with an element named ‘accept’ which is a logical vector whose ith element indicates whether the ith swap between adjacent tempered chains was accepted or not, and an element named 'at_temperature', an integer vector whose ith element indicates which pair of consecutive temperatures was the ith to be proposed for swapping (giving the lowest one).

An object of class `BeviMed_m`

.

Greene et al., A Fast Association Test for Identifying Pathogenic Variants Involved in Rare Diseases, The American Journal of Human Genetics (2017), http://dx.doi.org/10.1016/j.ajhg.2017.05.015.

[Package *BeviMed* version 5.8 Index]