Hello,

I used RSEM to extract gene and transcript level read count information for
our single end read libraries. Then rounded off the expected read counts to
use for differential expression analysis using edgeR at both transcript and
gene level. However, I found that the number of DE transcripts were almost
10 times less than those of genes.

 Is this expected or should I be following other package to analyze
transcript level DE analysis.

Appreciate any help/suggestions.

Thank you,
Alan

sessionInfo()

R version 3.0.1 (2013-05-16)
Platform: x86_64-w64-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] BiocInstaller_1.10.3 edgeR_3.2.3          limma_3.16.5

loaded via a namespace (and not attached):
[1] tools_3.0.1

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