consensus_partition_by_down_sampling {cola} | R Documentation |
Consensus partitioning only with a subset of columns
consensus_partition_by_down_sampling(data, subset = min(round(ncol(data)*0.2), 250), verbose = TRUE, prefix = "", anno = NULL, anno_col = NULL, dist_method = c("euclidean", "correlation", "cosine"), .env = NULL, ...)
data |
A numeric matrix where subgroups are found by columns. |
subset |
Number of columns to randomly sample, or a vector of selected indices. |
verbose |
Whether to print messages. |
prefix |
Internally used. |
anno |
Annotation data frame. |
anno_col |
Annotation colors. |
dist_method |
Method for predict the class for other columns. |
.env |
An environment, internally used. |
... |
All pass to |
The function performs consensus partitioning only with a small subset
of columns and the class of other columns are predicted by predict_classes,ConsensusPartition-method
.
## Not run: data(golub_cola) m = get_matrix(golub_cola) set.seed(123) golub_cola_ds = consensus_partition_by_down_sampling(m, subset = 50, anno = get_anno(golub_cola), anno_col = get_anno_col(golub_cola), top_value_method = "SD", partition_method = "kmeans") ## End(Not run)