count.DEnumber

0th

Percentile

Count the number of differentially expressed (DE) genes

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.
Details

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

Value

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

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

Aliases
  • count.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))
Documentation reproduced from package MetaDE, version 1.0.5, License: GPL-2

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