celdaGridSearch.RdYields assigments of genes/cells to clusters, depending on the provided model type.
celdaGridSearch(counts, model, params.test, params.fixed = NULL, max.iter = 200, nchains = 3, cores = 1, best.only = TRUE, seed = 12345, verbose = TRUE, logfile.prefix = "Celda")
| counts | A count matrix. |
|---|---|
| model | Celda model. Options available in `celda::available.models`. |
| params.test | List. A list denoting the combinations of parameters to run in a celda model. For example, "list(K=5:10, L=15:20)" will run all combinations of K from 5 to 10 and L from 15 to 20 in model 'celda_CG'. |
| params.fixed | List. A list denoting additional parameters to use in each celda model. Default NULL. |
| max.iter | Integer. Maximum number of iterations of Gibbs sampling to perform. Default 200. |
| nchains | Integer. Number of random cluster initializations. Default 1. |
| cores | Integer. The number of cores to use for parallel Gibbs sampling. Default 1. |
| best.only | Logical. Whether to return only the chain with the highest log likelihood per combination of parameters or return all chains. Default TRUE. |
| seed | Integer. Passed to set.seed(). Default 12345. |
| verbose | Logical. Whether to print log messages during celda chain execution. Default TRUE. |
| logfile.prefix | Character. Prefix for log files from worker threads and main process. Default "Celda". |
Object of class "celda_list", which contains results for all model parameter combinations and summaries of the run parameters
## Simulate a small dataset with 5 cell clusters and 10 feature modules celda.sim = simulateCells(model="celda_CG", K=5, L=10, G=100) ## Run various combinations of parameters with 'celdaGridSearch' cgs = celdaGridSearch(celda.sim$counts, model="celda_CG", params.test=list(K=4:6, L=9:11), params.fixed=list(sample.label=celda.sim$sample.label), best.only=TRUE, nchains=1)#>#>#>#>#> Error in { current.run = c(run.params[i, ]) chain.params = list() for (j in names(params.test)) { chain.params[[j]] = current.run[[j]] } chain.params$counts = counts chain.params$seed = all.seeds[ifelse(i%%nchains == 0, nchains, i%%nchains)] chain.params$max.iter = max.iter chain.params$nchain = 1 chain.params$count.checksum = count.checksum chain.params$verbose = verbose chain.params$logfile = paste0(logfile.prefix, "_", paste(paste(colnames(run.params), run.params[i, ], sep = "-"), collapse = "_"), "_Seed-", chain.params$seed, "_log.txt") res = do.call(model, c(chain.params, params.fixed)) return(list(res))}: task 1 failed - "unused argument (gamma)"