HeatmapGenerator is a graphical user interface software program written in C++, R, and OpenGL to create customized gene expression heatmaps from RNA-seq and microarray data in medical research with simple clicks of a button to help you (the researcher) save time and money.
HeatmapGenerator is free software (released under the GNU General Public License) and you are welcome (and encouraged) to contribute to it. Please feel free to get in touch with me at firstname.lastname@example.org, Github, or here on Biostars.
Giving wet-lab people an opportunity to make heatmaps directly in R without needing to know how to program in R is broadly useful for RNA-seq and microarray research. I've never seen programming languages get synthesized together like that before so I googled for "hybrid computational pipeline" and didn't come up with any more bioinformatics results besides for your paper. As far as I can tell, it's a whole new bioinformatics programming paradigm. As this software development style is likely to be of general interest to computational biologists, may I ask how you went about it and how you accomplished this hybridity (in layman's terms)?
All this reminds me of the Quilt plot and BoxPlotR papers. There is basically no problem with drawing a heatmap in R, it takes just several lines of code. heatmap.2 also handles all clustering stuff, and RStudio provides a nice GUI. Actually, creating heatmaps using R scripts has lots of benefits:
you can easily modify / pre-process the data
no need to leave R environment when working with differential expression analysis modules like edgeR
you can later re-run your R code, this provides analysis consistency
As for the "you don't need to have programming experience" thesis, those gene expression tables do not come from nowhere. You either learn how to program and perform all the analysis yourself, or ask the bioinformatician who has performed the analysis to help you with visualization, etc.