ELBOW

DOI: 10.18129/B9.bioc.ELBOW    

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

ELBOW - Evaluating foLd change By the lOgit Way

Bioconductor version: Release (3.13)

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 <justinzhang.xl at gmail.com>

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

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("ELBOW")

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

Documentation

PDF   Reference Manual

Details

biocViews GeneExpression, ImmunoOncology, Microarray, MultiChannel, OneChannel, RNASeq, Sequencing, Software, Technology, TwoChannel
Version 1.28.0
In Bioconductor since BioC 2.14 (R-3.1) (7.5 years)
License file LICENSE
Depends R (>= 2.15.0)
Imports graphics, stats, utils
LinkingTo
Suggests DESeq, GEOquery, limma, simpleaffy, affyPLM, RColorBrewer, hgu133plus2cdf, hgu133plus2probe
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package
Windows Binary
macOS 10.13 (High Sierra)
Source Repository git clone https://git.bioconductor.org/packages/ELBOW
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ELBOW
Package Short Url https://bioconductor.org/packages/ELBOW/
Package Downloads Report Download Stats

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: