To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("ELBOW")

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

ELBOW

 

ELBOW - Evaluating foLd change By the lOgit Way

Bioconductor version: Release (3.1)

Elbow an improved fold change test that uses cluster analysis and pattern recognition to set cut off limits that are derived directly from intrareplicate variance without assuming a normal distribution for as few as 2 biological replicates. Elbow also provides the same consistency as fold testing in cross platform analysis. Elbow has lower false positive and false negative rates than standard fold testing when both are evaluated using T testing and Statistical Analysis of Microarray using 12 replicates (six replicates each for initial and final conditions). Elbow provides a null value based on initial condition replicates and gives error bounds for results to allow better evaluation of significance.

Author: Xiangli Zhang, Natalie Bjorklund, Graham Alvare, Tom Ryzdak, Richard Sparling, Brian Fristensky

Maintainer: Graham Alvare <alvare at cc.umanitoba.ca>, Xiangli Zhang <zhangju at cc.umanitoba.ca>

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

Installation

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("ELBOW")

Documentation

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

browseVignettes("ELBOW")

 

PDF R Script Using ELBOW --- the definitive ELBOW tutorial
PDF   Reference Manual
Text   LICENSE

Details

biocViews GeneExpression, Microarray, MultiChannel, OneChannel, RNASeq, Sequencing, Software, Technology, TwoChannel
Version 1.4.0
In Bioconductor since BioC 2.14 (R-3.1) (1.5 years)
License file LICENSE
Depends R (>= 2.15.0)
Imports
LinkingTo
Suggests DESeq, GEOquery, limma, simpleaffy, affyPLM, RColorBrewer
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source ELBOW_1.4.0.tar.gz
Windows Binary ELBOW_1.4.0.zip
Mac OS X 10.6 (Snow Leopard) ELBOW_1.4.0.tgz
Mac OS X 10.9 (Mavericks) ELBOW_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/ELBOW/tree/release-3.1
Package Short Url http://bioconductor.org/packages/ELBOW/
Package Downloads Report Download Stats

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