I have RNA-seq data with 2 conditions and 3 replicates per conditions.

I ran the [New Tuxedo pipeline][1] and also created some [read count tables][2] with prepDE.

I analysed differentially expressed genes with `Ballgown` and `DESeq2`.

With a treshold of 1 log2FoldChange and 0.01 padj in `DESeq2`: 14400 /32000 (45%) of DE genes

With a treshold of 0.01 pval in `Ballgown`: 3678/32000 (of DE genes), even with no fold change treshold, the number of DE genes is (very) lower. In ballgown, what is the difference between qval and pval ? Which one corresponds to padj in DESeq2 ?

I expect many DE genes as conditions are very different biogically (testis vs ovary, same species).

Why do I have a so large difference between softwares?

  [1]: https://www.nature.com/articles/nprot.2016.095
  [2]: http://ccb.jhu.edu/software/stringtie/index.shtml?t=manual
*pval* is the nominal p-value. *qval* is the adjusted p-value, which are also known as q-values (not many people know this).

Ballgown may be using FPKM data when conducting the differential expression analysis. FPKM is not suitable for this purpose. Please confirm the type of normalisation that you used in Ballgown.

When you ran DESeq2, did you use the `lfcShrink()` function? - see the piece of code that I posted here: https://www.biostars.org/p/324128/#324305