SimBindProfiles

DOI: 10.18129/B9.bioc.SimBindProfiles    

This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see SimBindProfiles.

Similar Binding Profiles

Bioconductor version: 3.9

SimBindProfiles identifies common and unique binding regions in genome tiling array data. This package does not rely on peak calling, but directly compares binding profiles processed on the same array platform. It implements a simple threshold approach, thus allowing retrieval of commonly and differentially bound regions between datasets as well as events of compensation and increased binding.

Author: Bettina Fischer, Enrico Ferrero, Robert Stojnic, Steve Russell

Maintainer: Bettina Fischer <bef22 at cam.ac.uk>

Installation

To install this package, start R (version "3.6") and enter:

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

BiocManager::install("SimBindProfiles")

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("SimBindProfiles")

 

PDF	R Script	SimBindProfiles: Similar Binding Profiles, identifies common and unique regions in array genome tiling array data
PDF		Reference Manual

Details

biocViews	Microarray, Software
Version	1.22.0
In Bioconductor since	BioC 2.13 (R-3.0) (6 years)
License	GPL-3
Depends	R (>= 2.10), methods, Ringo
Imports	limma, mclust, Biobase
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Build Report

Package Archives

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

Source Package	SimBindProfiles_1.22.0.tar.gz
Windows Binary	SimBindProfiles_1.22.0.zip
Mac OS X 10.11 (El Capitan)	SimBindProfiles_1.22.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/SimBindProfiles
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/SimBindProfiles
Package Short Url	https://bioconductor.org/packages/SimBindProfiles/
Package Downloads Report	Download Stats