bioinformatist/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.

Getting started

Package details

Bioconductor views BatchEffect Classification Clustering DifferentialExpression FeatureExtraction GUI GeneExpression GeneSetEnrichment Microarray Normalization Preprocessing RNASeq Software Survival Visualization
Maintainer
LicenseGPL-3 | file LICENSE
Version0.99.27
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("bioinformatist/CrossICC")
bioinformatist/CrossICC documentation built on May 14, 2021, 10:46 a.m.