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.
This package is for version 3.1 of Bioconductor; for the stable, up-to-date release version, see EDDA.
Bioconductor version: 3.1
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")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("EDDA")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("EDDA")
R Script | EDDA Vignette | |
Reference Manual | ||
Text | NEWS |
biocViews | ChIPSeq, ExperimentalDesign, Normalization, RNASeq, Sequencing, Software |
Version | 1.6.0 |
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 |
Follow Installation instructions to use this package in your R session.
Package Source | EDDA_1.6.0.tar.gz |
Windows Binary | EDDA_1.6.0.zip (32- & 64-bit) |
Mac OS X 10.6 (Snow Leopard) | EDDA_1.6.0.tgz |
Mac OS X 10.9 (Mavericks) | EDDA_1.6.0.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/EDDA/tree/release-3.1 |
Package Short Url | http://bioconductor.org/packages/EDDA/ |
Package Downloads Report | Download Stats |
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