To install this package, start R and enter:

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

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

RankProd

 

   

Rank Product method for identifying differentially expressed genes with application in meta-analysis

Bioconductor version: Release (3.4)

Non-parametric method for identifying differentially expressed (up- or down- regulated) genes based on the estimated percentage of false predictions (pfp). The method can combine data sets from different origins (meta-analysis) to increase the power of the identification.

Author: Francesco Del Carratore <francesco.delcarratore at postgrad.manchester.ac.uk>, Andris Janckevics <andris.jankevics at gmail.com> Fangxin Hong <fxhong at jimmy.harvard.edu>, Ben Wittner <Wittner.Ben at mgh.harvard.edu>, Rainer Breitling <r.breitling at bio.gla.ac.uk>, and Florian Battke <battke at informatik.uni-tuebingen.de>

Maintainer: Francesco Del Carratore <francescodc87 at gmail.com>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("RankProd")

 

PDF R Script RankProd Tutorial
PDF   Reference Manual
Text   LICENSE

Details

biocViews DifferentialExpression, GeneExpression, GeneSignaling, Lipidomics, Metabolomics, Microarray, Proteomics, ResearchField, Software, StatisticalMethod, SystemsBiology
Version 3.0.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 11.5 years)
License file LICENSE
Depends R (>= 3.2.1), stats, methods, Rmpfr, gmp
Imports graphics
LinkingTo
Suggests
SystemRequirements
Enhances
URL
Depends On Me RNAither, tRanslatome
Imports Me HTSanalyzeR, synlet
Suggests Me oneChannelGUI
Build Report  

Package Archives

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

Package Source RankProd_3.0.0.tar.gz
Windows Binary RankProd_3.0.0.zip
Mac OS X 10.9 (Mavericks) RankProd_3.0.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/RankProd/tree/release-3.4
Package Short Url http://bioconductor.org/packages/RankProd/
Package Downloads Report Download Stats

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