dimension_reduction-ConsensusPartition-method {cola} | R Documentation |
Visualize samples (the matrix columns) after dimension reduction
## S4 method for signature 'ConsensusPartition' dimension_reduction(object, k, top_n = NULL, method = c("PCA", "MDS", "t-SNE", "UMAP"), control = list(), internal = FALSE, nr = 5000, silhouette_cutoff = 0.5, remove = FALSE, scale_rows = TRUE, verbose = TRUE, ...)
object |
A |
k |
Number of partitions. |
top_n |
Top n rows to use. By default it uses all rows in the original matrix. |
method |
Which method to reduce the dimension of the data. |
control |
|
internal |
Internally used. |
nr |
If number of matrix rows is larger than this value, random |
silhouette_cutoff |
Cutoff of silhouette score. Data points with values less than it will be mapped with cross symbols. |
remove |
Whether to remove columns which have less silhouette scores than the cutoff. |
scale_rows |
Whether perform scaling on matrix rows. |
verbose |
Whether print messages. |
... |
Other arguments. |
No value is returned.
Zuguang Gu <z.gu@dkfz.de>
data(cola_rl) dimension_reduction(cola_rl["sd", "kmeans"], k = 3)