EDDA-package {EDDA} | R Documentation

## 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<lij9@gis.a-star.edu.sg>, Luo Huaien<luoh2@gis.a-star.edu.sg>, Niranjan Nagarajan <nagarajann@gis.a-star.edu.sg>

### 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)

[Package EDDA version 1.26.0 Index]