consensus_partition_by_down_sampling: Consensus partitioning only with a subset of columns

In cola: A Framework for Consensus Partitioning

Description

Consensus partitioning only with a subset of columns

Usage

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, ...)

Arguments

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 consensus_partition.

Details

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.

Examples

## 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)

cola documentation built on Nov. 8, 2020, 8:12 p.m.