Reviewer response for version 1
Wang and Ma’ayan introduced an RNA-seq pipeline tutorial using IPython notebook and a Docker image. 
Specifically, the authors applied the pipeline to analyze data from a recent Zika virus study. 
The authors found that their pipeline not only confirms the down-regulated cell cycle genes, but also uncovers a set of genes with a biological function that potentially associated with a particular phenotype. 
While the work and context sound interesting, there are several concerns that need to be addressed or discussed:
- This reviewer really liked the approach that the authors have taken to showcase analysis. 
I wish more researchers adopt this methodology.
- This could be a great way to do additional analysis easily.. 
I wonder if authors can look into additional RNASeq pipelines and compare/contrast how Jupiter-friendly they are.
Minor comments:
The clustering (in Figure 1) is based on z-score and the 800 genes serve well to cluster the samples into two different groups. 
Was z-scores close to zero excluded as they are uninformative? 
Was FDR applied?
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