Renders probability and relative expression heatmaps to visualize the relationship between feature modules and cell populations.

It is often useful to visualize to what degree each feature influences each cell cluster. This can also be useful for identifying features which may be redundant or unassociated with cell clustering.

celdaProbabilityMap(counts, celda.mod, ...)

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 object of class "celda_C" or "celda_CG".
...	Additional parameters.

Examples

celda.sim = simulateCells("celda_CG")
celda.mod = celda_CG(celda.sim$counts, K=celda.sim$K, L=celda.sim$L,
                     nchains=1, max.iter=1)
#> --------------------------------------------------------------------
#> Starting Celda_CG: Clustering cells and genes.
#> --------------------------------------------------------------------
#> Thu Sep 06 12:55:49 2018 .. Initializing chain 1 with 'random' (seed=12345)
#> Thu Sep 06 12:55:49 2018 .... Determining if any cell clusters should be split.
#> Thu Sep 06 12:55:49 2018 .... Cluster 4 was reassigned and cluster 3 was split in two.
#> Thu Sep 06 12:55:49 2018 .... Determining if any gene clusters should be split.
#> Thu Sep 06 12:55:50 2018 .... Cluster 2 was reassigned and cluster 9 was split in two.
#> Thu Sep 06 12:55:50 2018 .... Completed iteration: 1 | logLik: -1272652.93151523
#> Thu Sep 06 12:55:50 2018 .. Finished chain 1 with seed 12345
#> --------------------------------------------------------------------
#> Completed Celda_CG. Total time: 0.75159 secs
#> --------------------------------------------------------------------
celdaProbabilityMap(celda.sim$counts, celda.mod)