Package: EDDA
Type: Package
Title: Experimental Design in Differential Abundance analysis
Version: 1.22.0
Date: 2015-01-06
Author: Li Juntao, Luo Huaien, Chia Kuan Hui Burton, Niranjan Nagarajan
Maintainer: Chia Kuan Hui Burton <chiakhb@gis.a-star.edu.sg>, Niranjan Nagarajan <nagarajann@gis.a-star.edu.sg>
Description: 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).
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
biocViews: ImmunoOncology, Sequencing, ExperimentalDesign,
        Normalization, RNASeq, ChIPSeq
URL: http://edda.gis.a-star.edu.sg/,
        http://genomebiology.com/2014/15/12/527
git_url: https://git.bioconductor.org/packages/EDDA
git_branch: RELEASE_3_9
git_last_commit: 3f55569
git_last_commit_date: 2019-05-02
Date/Publication: 2019-05-02
NeedsCompilation: yes
Packaged: 2019-05-03 02:49:41 UTC; biocbuild
Built: R 3.6.0; i386-w64-mingw32; 2019-05-03 13:16:13 UTC; windows
Archs: i386, x64
