Provides cluster assignments for all genes in a provided single-cell sequencing count matrix, using the celda Bayesian hierarchical model.
celda_G(counts, L, beta = 1, delta = 1, gamma = 1, max.iter = 25,
count.checksum = NULL, seed = 12345, y.split.on.iter = 3,
y.num.splits = 3, y.init = NULL, logfile = NULL, ...)A numeric count matrix
The number of clusters to generate
The Dirichlet distribution parameter for Phi; adds a pseudocount to each transcriptional state within each cell.
The Dirichlet distribution parameter for Eta; adds a gene pseudocount to the numbers of genes each state. Default to 1.
The Dirichlet distribution parameter for Psi; adds a pseudocount to each gene within each transcriptional state.
Maximum iterations of Gibbs sampling to perform. Defaults to 25.
An MD5 checksum for the provided counts matrix
Parameter to set.seed() for random number generation.
On every y.split.on.iter iteration, a heuristic will be applied using hierarchical clustering to determine if a gene cluster should be merged with another gene cluster and a third gene cluster should be split into two clusters. This helps avoid local optimum during the initialization. Default to be 3.
Maximum number of times to perform the heuristic described in y.split.on.iter.
Initial values of y. If NULL, y will be randomly sampled. Default NULL.
The name of the logfile to redirect messages to.
Additional parameters