To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("iGC")

In most cases, you don't need to download the package archive at all.

iGC

 

   

An integrated analysis package of Gene expression and Copy number alteration

Bioconductor version: Release (3.4)

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 ntu.edu.tw>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("iGC")

Documentation

HTML R Script Introduction to iGC
PDF   Reference Manual
Text   NEWS

Details

biocViews AssayDomain, Biological Question, CopyNumberVariation, DifferentialExpression, GeneExpression, Genetics, GenomicVariation, Microarray, MultipleComparison, ResearchField, Sequencing, Software, Technology, WorkflowStep
Version 1.4.0
In Bioconductor since BioC 3.2 (R-3.2) (1.5 years)
License GPL-2
Depends R (>= 3.2.0)
Imports plyr, data.table
LinkingTo
Suggests BiocStyle, knitr, rmarkdown
SystemRequirements
Enhances doMC
URL http://github.com/ccwang002/iGC
BugReports http://github.com/ccwang002/iGC/issues
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source iGC_1.4.0.tar.gz
Windows Binary iGC_1.4.0.zip
Mac OS X 10.9 (Mavericks) iGC_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/iGC/tree/release-3.4
Package Short Url http://bioconductor.org/packages/iGC/
Package Downloads Report Download Stats

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