plotROC: plot Receiver Operating Characteristic curve

Description Usage Arguments Author(s) References Examples

View source: R/plotROC.R

Description

plot Receiver Operating Characteristic curve for each test.

Usage

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plotROC(obj,DE.methods=c("Cuffdiff","DESeq","baySeq","edgeR","MetaStats","NOISeq"), 
	nor.methods=c("default","Mode","UQN","NDE"),
	plot_type = "o",plot_pch = 20,plot_lwd = 1.75,plot_cex = 1) 

Arguments

obj

Object from testDATs().

DE.methods

Method list for differential expression tests. Methods currently available include "Cuffdiff","DESeq","baySeq","edgeR","MetaStats","NOISeq".

nor.methods

Normalization method list. Methods currently available include "default"(default normalization for each DE method),"Mode"(Mode normalization),"UQN"(Upper quartile normalization),"NDE"(non-differential expression normalization).

plot_type

type option in plot.

plot_pch

pch option in plot.

plot_lwd

lwd option in plot.

plot_cex

cex option in plot.

Author(s)

Li Juntao and Chia Kuan Hui Burton

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

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

EDDA documentation built on May 31, 2017, 10:54 a.m.

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