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QUBIC

An R Package for Qualitative Biclustering in Support of Gene Co-Expression Analyses

Bioconductor version: 3.23 · Package version: 1.40.0

The core function of this R package is to provide the implementation of the well-cited and well-reviewed QUBIC algorithm, aiming to deliver an effective and efficient biclustering capability. This package also includes the following related functions: (i) a qualitative representation of the input gene expression data, through a well-designed discretization way considering the underlying data property, which can be directly used in other biclustering programs; (ii) visualization of identified biclusters using heatmap in support of overall expression pattern analysis; (iii) bicluster-based co-expression network elucidation and visualization, where different correlation coefficient scores between a pair of genes are provided; and (iv) a generalize output format of biclusters and corresponding network can be freely downloaded so that a user can easily do following comprehensive functional enrichment analysis (e.g. DAVID) and advanced network visualization (e.g. Cytoscape).

Installation

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

BiocManager::install("QUBIC")

Details

MaintainerYu Zhang <zy26@jlu.edu.cn>
AuthorYu Zhang [aut, cre], Qin Ma [aut]
LicenseCC BY-NC-ND 4.0 + file LICENSE
URLhttps://github.com/zy26/QUBIC
Bug Reportshttps://github.com/zy26/QUBIC/issues
System RequirementsC++11, Rtools (>= 3.1)
Downloads rank324
Source branchRELEASE_3_23
biocViewsClustering, DifferentialExpression, GeneExpression, Microarray, MultipleComparison, Network, Software, StatisticalMethod, Visualization

Documentation

Download

Dependencies

Depends: R (>= 4.5.0)

Imports: Rcpp (>= 0.11.0), methods, Matrix

LinkingTo: Rcpp, RcppArmadillo

Suggests: QUBICdata, qgraph, fields, knitr, rmarkdown

Enhances: RColorBrewer