Package: EDDA
Type: Package
Title: Experimental Design in Differential Abundance analysis
Version: 1.5.3
Date: 2015-01-13
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 is a tool for systematic assessment of the impact of experimental design and the statistical test used on the ability to detect differential abundance. EDDA can aid in the design of a range of common experiments such as RNA-seq, ChIP-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. More details of EDDA can be found at Luo, Huaien et al. "The Importance of Study Design for Detecting Differentially Abundant Features in High-Throughput Experiments." Genome Biology 2014;15(12):527 (http://www.ncbi.nlm.nih.gov/pubmed/25517037/). An accompanying web server (http://edda.gis.a-star.edu.sg/) is available for easy access to some functionality of EDDA.
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: Sequencing, ExperimentalDesign, Normalization, RNASeq,
        ChIPSeq
URL: http://csb5.github.io/EDDA/
Packaged: 2015-01-15 05:36:21 UTC; biocbuild
Built: R 3.1.2; i386-w64-mingw32; 2015-01-15 08:55:58 UTC; windows
Archs: i386, x64
