macat

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This package is for version 3.18 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see macat.

MicroArray Chromosome Analysis Tool


Bioconductor version: 3.18

This library contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. MACAT is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions. The functions have been tested on a publicly available data set about acute lymphoblastic leukemia (Yeoh et al.Cancer Cell 2002), which is provided in the library 'stjudem'.

Author: Benjamin Georgi, Matthias Heinig, Stefan Roepcke, Sebastian Schmeier, Joern Toedling

Maintainer: Joern Toedling <jtoedling at yahoo.de>

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

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("macat")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("macat")
MicroArray Chromosome Analysis Tool PDF R Script
Reference Manual PDF

Details

biocViews DifferentialExpression, Microarray, Software, Visualization
Version 1.76.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 19 years)
License Artistic-2.0
Depends Biobase, annotate
Imports
System Requirements
URL
See More
Suggests hgu95av2.db, stjudem
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package macat_1.76.0.tar.gz
Windows Binary macat_1.76.0.zip
macOS Binary (x86_64) macat_1.76.0.tgz
macOS Binary (arm64) macat_1.76.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/macat
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/macat
Package Short Url https://bioconductor.org/packages/macat/
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