EDDA-package: Experimental Design in Differential Abundance analysis

In EDDA: Experimental Design in Differential Abundance analysis

Description

EDDA aids in the design of a range of common experiments including 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.

Details

Package:	EDDA
Type:	Package
Version:	0.99.2
Date:	2014-02-12
License:	GPL (>= 2)

generateData() testDATs() computeAUC() plotROC() plotPRC()

Author(s)

Li Juntao, Luo Huaien, Chia Kuan Hui Burton, Niranjan Nagarajan

Maintainer: Li Juntao<[e-mail]>, Luo Huaien<[e-mail]>, Niranjan Nagarajan <[e-mail]>

References

Luo Huaien, Li Juntao,Chia Kuan Hui Burton, Shyam Prabhakar, Paul Robson, Niranjan Nagarajan, The importance of study design for detecting differentially abundant features in high-throughput experiments, under review.

Examples

data <- generateData(EntityCount=500)
test.obj <- testDATs(data,DE.methods=c("DESeq","edgeR"),nor.methods="default")
auc.obj  <- computeAUC(test.obj)
plotROC(auc.obj)
plotPRC(auc.obj)

EDDA documentation built on Nov. 8, 2020, 5:44 p.m.