Package: iGC 1.43.0

Liang-Bo Wang

iGC: An integrated analysis package of Gene expression and Copy number alteration

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

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

iGC_1.43.0.tar.gz
iGC_1.43.0.zip(r-4.7)iGC_1.43.0.zip(r-4.6)iGC_1.43.0.zip(r-4.5)
iGC_1.43.0.tgz(r-4.6-any)iGC_1.43.0.tgz(r-4.5-any)
iGC_1.43.0.tar.gz(r-4.7-any)iGC_1.43.0.tar.gz(r-4.6-any)
iGC_1.43.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
iGC/json (API)
NEWS

# Install 'iGC' in R:
install.packages('iGC', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ccwang002/igc/issues

Datasets:

On BioConductor:iGC-1.43.0(bioc 3.24)iGC-1.42.0(bioc 3.23)

softwarebiological questiondifferentialexpressiongenomicvariationassaydomaincopynumbervariationgeneexpressionresearchfieldgeneticstechnologymicroarraysequencingworkflowstepmultiplecomparison

3.78 score 1 stars 8 scripts 380 downloads 3 mentions 5 exports 3 dependencies

Last updated from:7cb644f3d4. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING142
linux-devel-x86_64NOTE164
source / vignettesOK178
linux-release-x86_64NOTE136
macos-release-arm64NOTE103
macos-oldrel-arm64NOTE109
windows-develNOTE86
windows-releaseNOTE79
windows-oldrelNOTE90
wasm-releaseOK119

Exports:create_gene_cnacreate_gene_expcreate_sample_descdirect_gene_cnafind_cna_driven_gene

Dependencies:data.tableplyrRcpp

Introduction to iGC

iGC Developers

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Jun 05 2026.

Last update: 2018-08-30
Started: 2015-09-14