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An integrated analysis package of Gene expression and Copy number alteration

Bioconductor version: Release (3.19)

This package is intended to identify differentially expressed genes driven by Copy Number Alterations from samples with both gene expression and CNA data.

Author: Yi-Pin Lai [aut], Liang-Bo Wang [aut, cre], Tzu-Pin Lu [aut], Eric Y. Chuang [aut]

Maintainer: Liang-Bo Wang <r02945054 at>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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:

Introduction to iGC HTML R Script
Reference Manual PDF


biocViews AssayDomain, Biological Question, CopyNumberVariation, DifferentialExpression, GeneExpression, Genetics, GenomicVariation, Microarray, MultipleComparison, ResearchField, Sequencing, Software, Technology, WorkflowStep
Version 1.34.0
In Bioconductor since BioC 3.2 (R-3.2) (9 years)
License GPL-2
Depends R (>= 3.2.0)
Imports plyr, data.table
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Suggests BiocStyle, knitr, rmarkdown
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Follow Installation instructions to use this package in your R session.

Source Package iGC_1.34.0.tar.gz
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macOS Binary (x86_64) iGC_1.34.0.tgz
macOS Binary (arm64) iGC_1.34.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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