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: 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>

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

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/
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