diceR: consensus_combine – R documentation

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consensus_combine

Combine algorithms

Description

Combines results for multiple objects from consensus_cluster() and outputs either the consensus matrices or consensus classes for all algorithms.

Usage

consensus_combine(..., element = c("matrix", "class"))

Arguments

`...`	any number of objects outputted from `consensus_cluster()`
`element`	either "matrix" or "class" to extract the consensus matrix or consensus class, respectively.

Details

This function is useful for collecting summaries because the original results from consensus_cluster were combined to a single object. For example, setting element = "class" returns a matrix of consensus cluster assignments, which can be visualized as a consensus matrix heatmap.

Value

consensus_combine returns either a list of all consensus matrices or a data frame showing all the consensus classes

Author(s)

Derek Chiu

Examples

# Consensus clustering for multiple algorithms
set.seed(911)
x <- matrix(rnorm(500), ncol = 10)
CC1 <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = "ap",
progress = FALSE)
CC2 <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = "km",
progress = FALSE)

# Combine and return either matrices or classes
y1 <- consensus_combine(CC1, CC2, element = "matrix")
str(y1)
y2 <- consensus_combine(CC1, CC2, element = "class")
str(y2)

diceR

Diverse Cluster Ensemble in R

v1.0.3

MIT + file LICENSE

Authors

Derek Chiu [aut, cre], Aline Talhouk [aut], Johnson Liu [ctb, com]

Initial release