celda Cell Clustering Model
celda_C(counts, sample.label = NULL, K, alpha = 1, beta = 1,
count.checksum = NULL, max.iter = 25, seed = 12345,
z.split.on.iter = 3, z.num.splits = 3, z.init = NULL, logfile = NULL,
...)A numeric count matrix
A vector indicating the sample for each cell (column) in the count matrix
An integer or range of integers indicating the desired number of cell clusters (for celda_C / celda_CG models)
Non-zero concentration parameter for sample Dirichlet distribution
Non-zero concentration parameter for gene Dirichlet distribution
An MD5 checksum for the provided counts matrix
Maximum iterations of Gibbs sampling to perform. Defaults to 25
Parameter to set.seed() for random number generation
On every "z.split.on.iter" iteration, a heuristic will be applied using hierarchical clustering to determine if a cell cluster should be merged with another cell cluster and a third cell cluster should be split into two clusters. This helps avoid local optimum during the initialization.
Maximum number of times to perform the heuristic described in z.split.on.iter
Initial values of z. If NULL, z will be randomly sampled. Default NULL.
If NULL, messages will be displayed as normal. If set to a file name, messages will be redirected messages to the file. Default NULL.
additonal parameters
An object of class celda_C with clustering results and Gibbs sampling statistics