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 Repository: CRAN Date/Publication: 2023-08-30 06:10:02 UTC