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The use case for this function is the following analysis: given per-exon p-values for null hypothesis H0, we can determine the number of genes in which at least for one exon H0 is rejected. What is the associated false disovery rate?

Usage

perGeneQValue(object, p = "pvalue", method = perGeneQValueExact)

Arguments

object

An DEXSeqResults object.

p

A character string indicating the name of the columns in DEXSeqResults from which to take the per-exon p-values.

method

Use the default value. This is for debugging only.

Details

Details

Value

A named numeric vector, values are per-gene q-values, names are gene.

Examples


  data(pasillaDEXSeqDataSet, package="pasilla")
  dxd <- estimateSizeFactors( dxd )
  dxd <- estimateDispersions( dxd )
  dxd <- testForDEU( dxd )
  dxr <- DEXSeqResults( dxd )

  perGeneQValue(dxr)
#>  FBgn0000256  FBgn0000578  FBgn0002921  FBgn0003089  FBgn0010226  FBgn0010280 
#> 3.983813e-12 2.252844e-08 2.259578e-02 1.000000e+00 1.000000e+00 5.973451e-01 
#>  FBgn0010638  FBgn0010808  FBgn0010909  FBgn0011300  FBgn0013811  FBgn0015278 
#> 1.000000e+00 9.938660e-01 0.000000e+00 5.204589e-01 1.000000e+00 1.000000e+00 
#>  FBgn0020309  FBgn0020372  FBgn0026777  FBgn0027084  FBgn0027579  FBgn0028341 
#> 1.613712e-03 1.000000e+00 1.000000e+00 1.000000e+00 3.968176e-03 1.000000e+00 
#>  FBgn0030170  FBgn0030302  FBgn0031108  FBgn0032003  FBgn0032785  FBgn0032979 
#> 1.000000e+00 9.703793e-01 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 
#>  FBgn0034158  FBgn0034180  FBgn0034420  FBgn0037050  FBgn0037683  FBgn0037926 
#> 3.720118e-01 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 
#>  FBgn0038725  FBgn0039776  FBgn0039914  FBgn0040297  FBgn0050460  FBgn0051021 
#> 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 5.891757e-02 9.908623e-01 
#>  FBgn0051352  FBgn0051790  FBgn0051847  FBgn0085442  FBgn0250871  FBgn0259735 
#> 1.000000e+00 1.000000e+00 1.000000e+00 1.104926e-09 1.000000e+00 1.000000e+00 
#>  FBgn0261573 
#> 3.617344e-03