Package: iGC 1.37.0

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_1.37.0.tar.gz
iGC_1.37.0.zip(r-4.5)iGC_1.37.0.zip(r-4.4)iGC_1.37.0.zip(r-4.3)
iGC_1.37.0.tgz(r-4.4-any)iGC_1.37.0.tgz(r-4.3-any)
iGC_1.37.0.tar.gz(r-4.5-noble)iGC_1.37.0.tar.gz(r-4.4-noble)
iGC_1.37.0.tgz(r-4.4-emscripten)iGC_1.37.0.tgz(r-4.3-emscripten)
iGC.pdf |iGC.html✨
iGC/json (API)
NEWS

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

Peer review:

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

Datasets:

On BioConductor:iGC-1.35.0(bioc 3.20)iGC-1.34.0(bioc 3.19)

softwarebiological questiondifferentialexpressiongenomicvariationassaydomaincopynumbervariationgeneexpressionresearchfieldgeneticstechnologymicroarraysequencingworkflowstepmultiplecomparison

3.78 score 1 stars 1 scripts 208 downloads 3 mentions 5 exports 3 dependencies

Last updated 23 days agofrom:9bbfe28571. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winNOTEOct 30 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winNOTEOct 30 2024
R-4.4-macNOTEOct 30 2024
R-4.3-winNOTEOct 30 2024
R-4.3-macNOTEOct 30 2024

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 Oct 30 2024.

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