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.
Value
consensus_combine returns either a list of all consensus matrices
or a data frame showing all the consensus classes
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.
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)
#> List of 2
#> $ 3:List of 2
#> ..$ AP: num [1:50, 1:50] 1 0.429 0.167 0.429 1 ...
#> ..$ KM: num [1:50, 1:50] 1 0.625 0 0.429 1 ...
#> $ 4:List of 2
#> ..$ AP: num [1:50, 1:50] 1 0.143 0.167 0 1 ...
#> ..$ KM: num [1:50, 1:50] 1 0.25 0 0.125 1 ...
y2 <- consensus_combine(CC1, CC2, element = "class")
str(y2)
#> List of 2
#> $ 3: int [1:50, 1:2] 1 1 2 1 1 1 2 1 3 2 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : NULL
#> .. ..$ : chr [1:2] "AP" "KM"
#> $ 4: int [1:50, 1:2] 1 2 3 2 1 2 3 3 4 3 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : NULL
#> .. ..$ : chr [1:2] "AP" "KM"