mpgex_cluster_bayes: Cluster similar methylation profiles using Gibbs smapling

Description Usage Arguments Examples

Description

mpgex_cluster is a wrapper function that clusters similar methylation profiles using the Gibbs sampling algorithm. Initially, it performs parameter checking, and initializes main parameters, such as mixing proportions, basis function coefficients, then Gibbs is applied and finally model selection metrics are calculated, such as BIC and AIC.

Usage

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mpgex_cluster_bayes(x, K = 3, pi_k = NULL, w = NULL, basis = NULL,
  w_0_mean = NULL, w_0_cov = NULL, gibbs_nsim = 5000,
  gibbs_burn_in = 1000, opt_method = "CG", opt_itnmax = 50,
  is_parallel = TRUE, no_cores = NULL, is_verbose = FALSE)

Arguments

x

A list of elements of length N, where each element is an L x 3 matrix of observations, where 1st column contains the locations. The 2nd and 3rd columns contain the total trials and number of successes at the corresponding locations, repsectively.

K

Integer denoting the number of clusters K.

pi_k

Vector of length K, denoting the mixing proportions.

w

A MxK matrix, where each column contains the basis function coefficients for the corresponding cluster.

basis

A 'basis' object. E.g. see polynomial.object

w_0_mean

The prior mean hyperparameter for w

w_0_cov

The prior covariance hyperparameter for w

gibbs_nsim

Argument giving the number of simulations of the Gibbs sampler.

gibbs_burn_in

Argument giving the burn in period of the Gibbs sampler.

opt_method

Optimization method used.

opt_itnmax

Optimization iterations for obtaining the initial EM parameter values.

is_parallel

Logical, indicating if code should be run in parallel.

no_cores

Number of cores to be used, default is max_no_cores - 1.

is_verbose

Logical, print results during EM iterations

Examples

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set.seed(123)
ex_data <- bpr_data
mpgex_clust <- mpgex_cluster_bayes(x = ex_data, gibbs_nsim = 20, gibbs_burn_in = 10,
                                   is_parallel = FALSE, opt_itnmax = 10)

andreaskapou/mpgex documentation built on May 12, 2019, 3:33 a.m.