CRAN/E | ccml

ccml

Consensus Clustering for Different Sample Coverage Data

Installation

About

Consensus clustering, also called meta-clustering or cluster ensembles, has been increasingly used in clinical data. Current consensus clustering methods tend to ensemble a number of different clusters from mathematical replicates with similar sample coverage. As the fact of common variety of sample coverage in the real-world data, a new consensus clustering strategy dealing with such biological replicates is required. This is a two-step consensus clustering package, which is used to input multiple predictive labels with different sample coverage (missing labels).

Key Metrics

Version 1.4.0
R ≥ 3.5.0
Published 2023-08-30 252 days ago
Needs compilation? no
License GPL-2
CRAN checks ccml results
Language en-US

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Maintainer

Maintainer

Chuanxing Li

chuan-xing.li@ki.se

Authors

Chuanxing Li

aut / cre

Meng Zhou

aut

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ccml archive

Depends

R ≥ 3.5.0

Imports

ggplot2
diceR
parallel
tidyr
SNFtool
plyr
ConsensusClusterPlus ≥ 1.56.0

Suggests

spelling
testthat ≥ 3.0.0