Function to fit the Bayesian Sparse Latent Factor Model to a group of data matrices within a directory. All matrices are supposed to have values representing the gene expression observed for different genes (rows) and different samples (columns).
slfm_list(
path = ".",
recursive = TRUE,
a = 2.1,
b = 1.1,
gamma_a = 1,
gamma_b = 1,
omega_0 = 0.01,
omega_1 = 10,
sample = 1000,
burnin = round(0.25 * sample),
lag = 1,
degenerate = FALSE
)path to the directory where the target data matrices are located.
logical argument (default = TRUE) indicating whether the function should look recursively inside folders.
positive shape parameter of the Inverse Gamma prior distribution (default = 2.1).
positive scale parameter of the Inverse Gamma prior distribution (default = 1.1).
positive 1st shape parameter of the Beta prior distribution (default = 1).
positive 2nd shape parameter of the Beta prior distribution (default = 1).
prior variance of the spike mixture component (default = 0.01).
prior variance of the slab mixture component (default = 10).
sample size to be considered for inference after the burn in period (default = 1000).
size of the burn in period in the MCMC algorithm (default = sample/4).
lag to build the chains based on spaced draws from the Gibbs sampler (default = 1).
logical argument (default = FALSE) indicating whether to use the degenerate version of the mixture prior for the factor loadings.
slfm, process_matrix, plot_matrix