EDDA

DOI: 10.18129/B9.bioc.EDDA    

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

This package is for version 3.13 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see EDDA.

Experimental Design in Differential Abundance analysis

Bioconductor version: Release (3.13)

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>

Installation

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

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

BiocManager::install("EDDA")

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

Documentation

PDF		Reference Manual

Details

biocViews	ChIPSeq, ExperimentalDesign, ImmunoOncology, Normalization, RNASeq, Sequencing, Software
Version	1.30.0
In Bioconductor since	BioC 2.14 (R-3.1) (7.5 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
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/EDDA
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/EDDA
Package Short Url	https://bioconductor.org/packages/EDDA/
Package Downloads Report	Download Stats