Package: ccml
Type: Package
Title: Consensus Clustering for Different Sample Coverage Data
Version: 1.4.0
Authors@R: c(
    person(given = "Chuanxing", family = "Li", email = "chuan-xing.li@ki.se", role = c("aut", "cre")),
  person(given = "Meng", family = "Zhou", email="zhoumeng@wmu.edu.cn", role="aut"))
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). 
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
Depends: R (>= 3.5.0)
Imports: ggplot2, diceR, parallel, tidyr, SNFtool, plyr,
        ConsensusClusterPlus (>= 1.56.0)
Suggests: spelling, testthat (>= 3.0.0)
Language: en-US
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2023-08-30 02:20:32 UTC; Lenovo
Author: Chuanxing Li [aut, cre],
  Meng Zhou [aut]
Maintainer: Chuanxing Li <chuan-xing.li@ki.se>
Repository: CRAN
Date/Publication: 2023-08-30 06:10:02 UTC
Built: R 4.2.0; ; 2023-08-31 12:52:44 UTC; unix
