TPEA: Statistical test and calculate the significance

Description Usage Arguments Details Value Author(s) Examples

View source: R/TPEA.R

Description

Comparing with the AUEC_R which the interested gene set extract from the background gene set randomly and the corresponding AUEC based on interested gene set you input. The last step is to calculate the significance.

Usage

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TPEA(DEGs, scores, n, FDR_method)

Arguments

DEGs

Interested gene set such as differentailly expressed gene set.

scores

The "AUEC" based on the interested gene set of 109 pathways.

n

Randomly number,e.g. 1000, 5000.

FDR_method

The methods of calculating FDR value,e.g. "fdr","BH","BY" ,"bonferroni" and etc..

Details

To calculate the significance of the result, you can set "n" as "1000" or any other number you want.

Value

The ultimately result of this topology-based enrichment analysis method.

Author(s)

Wei Jiang

Examples

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##Randomly generated interested gene set
ViewLatestTime()
##If you want to use the latest information,please run "UPDATE()".
DEGs<-sample(100:10000,10);
DEG<-as.matrix(DEGs);
##Set the times of perturbation
number<-50;
##Calculate the observed statistic
scores<-AUEC(DEG);
##Significant computational
FDR_method<-"fdr";
results<-TPEA(DEG,scores,number,FDR_method);

TPEA documentation built on June 25, 2017, 5:02 p.m.