Bioconductor version: Release (3.6)
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.
Author: Nathan Lawlor [aut, cre], Peiyong Guan [aut], Alec Fabbri [aut], Krish Karuturi [aut], Joshy George [aut]
Maintainer: Nathan Lawlor <nathan.lawlor03 at gmail.com>
Citation (from within R,
enter citation("multiClust")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("multiClust")
HTML | R Script | A Guide to multiClust |
Reference Manual | ||
Text | NEWS |
biocViews | Clustering, FeatureExtraction, GeneExpression, Software, Survival |
Version | 1.8.2 |
In Bioconductor since | BioC 3.3 (R-3.3) (2 years) |
License | GPL (>= 2) |
Depends | |
Imports | mclust, ctc, survival, cluster, dendextend, amap, graphics, grDevices |
LinkingTo | |
Suggests | knitr, gplots, RUnit, BiocGenerics, preprocessCore, Biobase, GEOquery |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | multiClust_1.8.2.tar.gz |
Windows Binary | multiClust_1.8.2.zip |
Mac OS X 10.11 (El Capitan) | multiClust_1.8.2.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/multiClust |
Package Short Url | http://bioconductor.org/packages/multiClust/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.6 | Source Archive |
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