To install this package, start R and enter:

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

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

EDDA

   

Experimental Design in Differential Abundance analysis

Bioconductor version: 3.2

EDDA can aid in the design of a range of common experiments such as RNA-seq, Nanostring assays, RIP-seq and Metagenomic sequencing, and enables researchers to comprehensively investigate the impact of experimental decisions on the ability to detect differential abundance. This work was published on 3 December 2014 at Genome Biology under the title "The importance of study design for detecting differentially abundant features in high-throughput experiments" (http://genomebiology.com/2014/15/12/527).

Author: Li Juntao, Luo Huaien, Chia Kuan Hui Burton, Niranjan Nagarajan

Maintainer: Chia Kuan Hui Burton <chiakhb at gis.a-star.edu.sg>, Niranjan Nagarajan <nagarajann at gis.a-star.edu.sg>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("EDDA")

 

PDF EDDA Vignette
PDF   Reference Manual
Text   NEWS

Details

biocViews ChIPSeq, ExperimentalDesign, Normalization, RNASeq, Sequencing, Software
Version 1.8.0
In Bioconductor since BioC 2.14 (R-3.1) (2 years)
License GPL (>= 2)
Depends Rcpp (>= 0.10.4), parallel, methods, ROCR, DESeq, baySeq, snow, edgeR
Imports graphics, stats, utils, parallel, methods, ROCR, DESeq, baySeq, snow, edgeR
LinkingTo Rcpp
Suggests
SystemRequirements
Enhances
URL http://edda.gis.a-star.edu.sg/ http://genomebiology.com/2014/15/12/527
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source EDDA_1.8.0.tar.gz
Windows Binary EDDA_1.8.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) EDDA_1.8.0.tgz
Mac OS X 10.9 (Mavericks) EDDA_1.8.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/EDDA/tree/release-3.2
Package Short Url http://bioconductor.org/packages/EDDA/
Package Downloads Report Download Stats

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