Hello,

I run the new protocol (HISAT, StringTie, Ballgown) with 24 samples (13 unaffected vs 11 affected) to get differential expression. After run R package in Ballgown, I got only 4 genes with a qval under 0.05. My goal is to perform a pathway analysis, but with only 4 genes there is no possible to do that. I was also trying to figure out how ballgown is calculating fold change. Because, I would also like to know which of these are up or down regulated. But I don't know how is the relationship log2(affected/unaffected) or log2(unaffected/affected). When I got the FPKM values and I tried to get the value of log2(a/u), fold change from the results are close but are not the same. My main concern is about qval, I run the same bam file from hisat in cuffdiff and I get more than 3000 significant genes. And even running DESeq from gtf file from stringtie i got around 700 significant genes. For this reason, I don't think quality of the samples could be the problem. Any idea why am I getting only 4 genes?

Thank you 

I have the same issue too. Does it have to do with more stringent value set for FDR? I get comparable results when the FDR is set <0.001 in cudiff. How one sets the FDR in Ballgown?

Hi, 

I have the same issue. I have RNA seq data for 3 genotypes and 3 cell types. Each cell type has 3 replicates (27 samples in total). When i do pairwise comparisons (one genotype to another for the same cell type), i get very few genes with qvalue less then 0.05. But when i do full model (effect of genotype) then i get many genes with q<0.05. What can be a solution in this case?