I have performed the Differential gene expression analysis based on 2 samples (one sample is controlled and the other is treated) using Noiseq. We do not have biological replicates (although its good to have). The output of Noiseq looks like:

Genes   Mock_mean   Treated_mean    M   D   prob    ranking
ENSGALG00000030907  0.091327389678701   834.11880142495 -13.1569176585108   834.027474035271    0.999997697497179   -834.13124382673
ENSGALG00000027716  4.63590810551782    3033.93990829454    -9.35412482674646   3029.30400018903    0.999997697497179   -3029.31844235836
ENSGALG00000046192  4.06351010806234    3218.73882138174    -9.62955331840357   3214.67531127368    0.999997697497179   -3214.68973389496

Column M reffers to the log2-ratio of the two conditions whereas column D is the value of the difference between conditions. Now I am interested to generate the heatmap. In Deseq2 we identify the top variable genes :

topVarGenes <- head(order(rowVars(assay(rld)), decreasing=TRUE ), 50 )

And then plot the heatmap:

heatmap.2( assay(rld)[ topVarGenes, ], scale="none",
       trace="none", dendrogram="column",
       col = colorRampPalette((brewer.pal(9, "GnBu")) )(100),
       ColSideColors = c( Control="gray", DPN="darkgreen", OHT="orange" )[
         colData(rld)$condition ] )

I have tried to extract the to 20 genes based on D:

select <- order(mynoiseq_tmm$D,decreasing=T)[1:20]

But I am not sure how to plot the heatmap in case of Noiseq. Any help will be highly appreciated.