celda_G.RdProvides 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, stop.iter = 10, max.iter = 200, split.on.iter = 10, split.on.last = TRUE, seed = 12345, nchains = 3, initialize = c("random", "split"), count.checksum = NULL, y.init = NULL, logfile = NULL, verbose = TRUE)
| counts | Integer matrix. Rows represent features and columns represent cells. |
|---|---|
| L | Integer. Number of feature modules. |
| beta | Numeric. Concentration parameter for Phi. Adds a pseudocount to each feature module in each cell. Default 1. |
| delta | Numeric. Concentration parameter for Psi. Adds a pseudocount to each feature in each module. Default 1. |
| gamma | Numeric. Concentration parameter for Eta. Adds a pseudocount to the number of features in each module. Default 1. |
| stop.iter | Integer. Number of iterations without improvement in the log likelihood to stop inference. Default 10. |
| max.iter | Integer. Maximum number of iterations of Gibbs sampling to perform. Default 200. |
| split.on.iter | Integer. On every `split.on.iter` iteration, a heuristic will be applied to determine if a feature module should be reassigned and another feature module should be split into two clusters. To disable splitting, set to -1. Default 10. |
| split.on.last | Integer. After the the chain has converged, according to `stop.iter`, a heuristic will be applied to determine if a cell population should be reassigned and another cell population should be split into two clusters. If a split occurs, then 'stop.iter' will be reset. Default TRUE. |
| seed | Integer. Passed to set.seed(). Default 12345. |
| nchains | Integer. Number of random cluster initializations. Default 1. |
| initialize | Chararacter. One of 'random' or 'split'. With 'random', features are randomly assigned to a clusters. With 'split' cell and feature clusters will be recurssively split into two clusters using `celda_G` until the specified L is reached. Default 'random'. |
| count.checksum | Character. An MD5 checksum for the `counts` matrix. Default NULL. |
| y.init | Integer vector. Sets initial starting values of y. If NULL, starting values for each feature will be randomly sampled from 1:L. 'y.init' can only be used when 'initialize' = "random". Default NULL. |
| logfile | Character. Messages will be redirected to a file named `logfile`. If NULL, messages will be printed to stdout. Default NULL. |
| verbose | Logical. Whether to print log messages. Default TRUE. |
An object of class celda_G with clustering results and various sampling statistics.
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