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ccml
View on CRAN: Click
here
Download and install ccml package within the R console
Install from CRAN:
install.packages("ccml")
Install from Github:
library("remotes")
install_github("cran/ccml") Install by package version:
library("remotes")
install_version("ccml", "1.4.0") Attach the package and use:
library("ccml")
Maintained by
Chuanxing Li
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-08-18
Latest Update:
Description:
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).
How to cite:
Chuanxing Li (2022). ccml: Consensus Clustering for Different Sample Coverage Data. R package version 1.4.0, https://cran.r-project.org/web/packages/ccml. Accessed 06 Jun. 2026.
Previous versions and publish date:
Other packages that cited ccml R package
View ccml citation profile
Other R packages that ccml depends,
imports, suggests or enhances
Complete documentation for ccml
Functions, R codes and Examples using
the ccml R package
Some associated functions: callNCW . ccml . example_data . plotCompareCW . randConsensusMatrix . spectralClusteringAffinity .
Some associated R codes: callNCW.R . ccml.R . example_data.R . globals.R . plotCompareCW.R . randConsensusMatrix.R . spectralClusteringAffinity.R . Full ccml package functions and examples
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