CrossICC: An Interactive Consensus Clustering Framework for Multi-platform Data Analysis

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.

Package details

AuthorYu Sun [aut, cre] (<>), Qi Zhao [aut] (<>)
Bioconductor views BatchEffect Classification Clustering DifferentialExpression FeatureExtraction GUI GeneExpression GeneSetEnrichment Microarray Normalization Preprocessing RNASeq Software Survival Visualization
MaintainerYu Sun <>
LicenseGPL-3 | file LICENSE
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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CrossICC documentation built on April 29, 2020, 4:40 a.m.