CrossICC

DOI: 10.18129/B9.bioc.CrossICC    

This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see CrossICC.

An Interactive Consensus Clustering Framework for Multi-platform Data Analysis

Bioconductor version: 3.12

CrossICC utilizes an iterative strategy to derive the optimal gene set and cluster number from consensus similarity matrix generated by consensus clustering and it is able to deal with multiple cross platform datasets so that requires no between-dataset normalizations. This package also provides abundant functions for visualization and identifying subtypes of cancer. Specially, many cancer-related analysis methods are embedded to facilitate the clinical translation of the identified cancer subtypes.

Author: Yu Sun <suny226 at mail2.sysu.edu.cn>, Qi Zhao <zhaoqi at sysucc.org.cn>

Maintainer: Yu Sun <suny226 at mail2.sysu.edu.cn>

Citation (from within R, enter citation("CrossICC")):

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("CrossICC")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

PDF   Reference Manual

Details

biocViews BatchEffect, Classification, Clustering, DifferentialExpression, FeatureExtraction, GUI, GeneExpression, GeneSetEnrichment, Microarray, Normalization, Preprocessing, RNASeq, Software, Survival, Visualization
Version 1.4.0
In Bioconductor since BioC 3.10 (R-3.6) (1.5 years)
License GPL-3 | file LICENSE
Depends R (>= 3.5), MASS
Imports data.table, methods, MergeMaid, ConsensusClusterPlus, limma, cluster, dplyr, Biobase, grDevices, stats, graphics, utils
LinkingTo
Suggests rmarkdown, testthat, knitr, shiny, shinydashboard, shinyWidgets, shinycssloaders, DT, ggthemes, ggplot2, pheatmap, RColorBrewer, tibble, ggalluvial
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary
macOS 10.13 (High Sierra)
Source Repository git clone https://git.bioconductor.org/packages/CrossICC
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CrossICC
Package Short Url https://bioconductor.org/packages/CrossICC/
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