MetaDE (version 1.0.5)

count.DEnumber: Count the number of differentially expressed (DE) genes

Description

a function to summary the number of DE genes at given p-value or FDR thresholds.

Usage

count.DEnumber(result, p.cut, q.cut)

Arguments

result

A p-value matrix or an object file from metaDE.pvalue,metaDE.minMCC, metaDE.ES

p.cut

a numeric vecter to specify the p-value thresholds at which the DE number is counted.

q.cut

a numeric vecter to specify the FDR thresholds at which the DE number is counted.

Value

• a list with components:
• pval.table
  a table contains the DE numbers counted at given p-value thresholds.
• FDR.table
  a table contains the DE numbers counted at given FDR thresholds.

Details

To count the DE number at FDR thresholds, the p-values were corrected by Benjamini-Hochberg procedure.

References

Benjamini Y, Hochberg Y: Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B-Methodological 1995, 57(1):289-300.

See Also

draw.DEnumber

Examples

#---example 1: Meta analysis of Differentially expressed genes between two classes----------#
label1<-rep(0:1,each=5)
label2<-rep(0:1,each=5)
exp1<-cbind(matrix(rnorm(5*200),200,5),matrix(rnorm(5*200,2),200,5))
exp2<-cbind(matrix(rnorm(5*200),200,5),matrix(rnorm(5*200,1.5),200,5))
x<-list(list(exp1,label1),list(exp2,label2))

# here I used modt to generate p-values. 
DEgene<-ind.analysis(x,ind.method=rep("regt",2),tail="abs",nperm=100)

#--then you can use Fisher's method to combine the above p-values
res<-MetaDE.pvalue(DEgene,meta.method='Fisher')
draw.DEnumber(res,FDR=TRUE,maxcut=0.1)
count.DEnumber(res,p.cut=c(0.01,0.05),q.cut=c(0.01,0.05))