This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see CrossICC.
Bioconductor version: 3.11
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 [aut, cre] , Qi Zhao [aut]
Maintainer: Yu Sun <suny226 at mail2.sysu.edu.cn>
Citation (from within R,
enter citation("CrossICC")
):
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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CrossICC")
HTML | R Script | How to use CrossICC? |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | BatchEffect, Classification, Clustering, DifferentialExpression, FeatureExtraction, GUI, GeneExpression, GeneSetEnrichment, Microarray, Normalization, Preprocessing, RNASeq, Software, Survival, Visualization |
Version | 1.2.0 |
In Bioconductor since | BioC 3.10 (R-3.6) (1 year) |
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 |
Follow Installation instructions to use this package in your R session.
Source Package | CrossICC_1.2.0.tar.gz |
Windows Binary | CrossICC_1.2.0.zip |
macOS 10.13 (High Sierra) | CrossICC_1.2.0.tgz |
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/ |
Package Downloads Report | Download Stats |
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