feature_map {ccfindR} | R Documentation |
Generate heatmap of features derived from factorization of count data.
feature_map(object, basis.matrix = NULL, rank, markers = NULL, subtract.mean = TRUE, log = TRUE, max.per.cluster = 10, feature.names = NULL, perm = NULL, main = "Feature map", cscale = NULL, cex.cluster = 1, cex.feature = 0.5, mar = NULL, ...)
object |
Object of class |
basis.matrix |
Basis matrix can be supplied instead of |
rank |
Rank value for which the gene map is to be displayed.
The object must contain the corresponding slot (one element of
|
markers |
Vector of gene names containing markers to be included
in addition to the metagenes. All entries of |
subtract.mean |
Process each rows of basis matrix |
log |
If |
max.per.cluster |
Maximum number of metagenes per cluster. |
feature.names |
Names to be used in the plot for features. |
perm |
Permutation of cluster IDs. |
main |
Main title. |
cscale |
Colors for heatmap. |
cex.cluster |
Cluster ID label size. |
cex.feature |
Feature ID label size. |
mar |
Margins for |
... |
This function uses image()
and is more flexible than
gene_map
.
If object
contains multiple ranks, only the requested
rank's basis matrix W will be displayed. As in gene_map
, the features
displayed in rows are selected by "max" scheme
NULL
set.seed(1) x <- simulate_data(nfeatures=10,nsamples=c(20,20,60)) rownames(x) <- seq_len(10) set.seed(1) x <- simulate_data(nfeatures=10,nsamples=c(20,20,60)) rownames(x) <- seq_len(10) colnames(x) <- seq_len(100) s <- scNMFSet(count=x,rowData=seq_len(10), colData=seq_len(100)) s <- vb_factorize(s,ranks=seq(2,5)) plot(s) feature_map(s, rank=3)