Get the probability of the cluster assignments generated during a celda run.

clusterProbability(counts, celda.mod, log = FALSE)

Arguments

counts

Integer matrix. Rows represent features and columns represent cells. This matrix should be the same as the one used to generate `celda.mod`.

celda.mod

Celda model. Options available in `celda::available.models`.

log

Logical. If FALSE, then the normalized conditional probabilities will be returned. If TRUE, then the unnormalized log probabilities will be returned. Default FALSE.

Examples

celda.sim = simulateCells("celda_CG") celda.mod = celda_CG(celda.sim$counts, K=celda.sim$K, L=celda.sim$L, nchains=1, max.iter=1)
#> --------------------------------------------------------------------
#> Starting Celda_CG: Clustering cells and genes.
#> --------------------------------------------------------------------
#> Thu Sep 06 12:56:43 2018 .. Initializing chain 1 with 'random' (seed=12345)
#> Thu Sep 06 12:56:43 2018 .... Determining if any cell clusters should be split.
#> Thu Sep 06 12:56:43 2018 .... Cluster 4 was reassigned and cluster 3 was split in two.
#> Thu Sep 06 12:56:43 2018 .... Determining if any gene clusters should be split.
#> Thu Sep 06 12:56:44 2018 .... Cluster 2 was reassigned and cluster 9 was split in two.
#> Thu Sep 06 12:56:44 2018 .... Completed iteration: 1 | logLik: -1272652.93151523
#> Thu Sep 06 12:56:44 2018 .. Finished chain 1 with seed 12345
#> --------------------------------------------------------------------
#> Completed Celda_CG. Total time: 0.514704 secs
#> --------------------------------------------------------------------
cluster.prob = clusterProbability(celda.sim$counts, celda.mod)