Package: multiClust
Type: Package
Title: multiClust: An R-package for Identifying Biologically Relevant
        Clusters in Cancer Transcriptome Profiles
Version: 1.40.0
Date: 2021-07-27
Authors@R: c(
    person("Nathan","Lawlor", email = "nathan.lawlor03@gmail.com",
    role = c("aut", "cre")),
    person("Peiyong", "Guan", role = "aut"),
    person("Alec","Fabbri", email = "fabbrialhs@gmail.com", role = "aut"),
    person("Krish", "Karuturi", email = "Krishna.Karuturi@jax.org",
    role = "aut"),
    person("Joshy", "George", email = "Joshy.George@jax.org", role = "aut")
    )
Description: Clustering is carried out to identify patterns in
        transcriptomics profiles to determine clinically relevant
        subgroups of patients. Feature (gene) selection is a critical
        and an integral part of the process. Currently, there are many
        feature selection and clustering methods to identify the
        relevant genes and perform clustering of samples. However,
        choosing an appropriate methodology is difficult. In addition,
        extensive feature selection methods have not been supported by
        the available packages. Hence, we developed an integrative
        R-package called multiClust that allows researchers to
        experiment with the choice of combination of methods for gene
        selection and clustering with ease. Using multiClust, we
        identified the best performing clustering methodology in the
        context of clinical outcome. Our observations demonstrate that
        simple methods such as variance-based ranking perform well on
        the majority of data sets, provided that the appropriate number
        of genes is selected. However, different gene ranking and
        selection methods remain relevant as no methodology works for
        all studies.
License: GPL (>= 2)
biocViews: FeatureExtraction, Clustering, GeneExpression, Survival
Imports: mclust, ctc, survival, cluster, dendextend, amap, graphics,
        grDevices
Suggests: knitr, rmarkdown, gplots, RUnit, BiocGenerics,
        preprocessCore, Biobase, GEOquery
VignetteBuilder: knitr
RoxygenNote: 5.0.0
NeedsCompilation: no
Author: Nathan Lawlor [aut, cre], Peiyong Guan [aut], Alec Fabbri
        [aut], Krish Karuturi [aut], Joshy George [aut]
Maintainer: Nathan Lawlor <nathan.lawlor03@gmail.com>
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-10-29 14:28:47 UTC
RemoteUrl: https://github.com/bioc/multiClust
RemoteRef: RELEASE_3_22
RemoteSha: 9efff1cf20a7d9a3f6791c78d574c381d2c2e989
Packaged: 2025-11-11 16:01:22 UTC; root
Built: R 4.5.2; ; 2025-11-11 16:08:18 UTC; windows
