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>, Qi Zhao <zhaoqi at>

Maintainer: Yu Sun <suny226 at>

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


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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
Suggests rmarkdown, testthat, knitr, shiny, shinydashboard, shinyWidgets, shinycssloaders, DT, ggthemes, ggplot2, pheatmap, RColorBrewer, tibble, ggalluvial
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