I wonder if she would have better, faster, or more insightful results of she uses A.I. (artificial intelligence)/Deep Learning and AI-chips (or GPUs) instead of super-computing. It's the latest stuff coming out of Silicon Valley and is supposedly more efficient in pattern recognition and optimal solution seeking. I'm far from an expert, but perhaps someone on here knows more about that field and could provide some insight.
Ultimately it goes back to having a lot of data and being confident that it's labeled correctly. The software makes everything else pretty easy. I see how Stanford is generating large datasets, but nobody is looking at using ML yet as far as I know.
It's funny they talk about biomarkers in these complex diseases, but you could train a classifier to identify other autoimmune diseases like Crohn's, UC, RA, and others maybe 90-95% of the time without a powerful machine or even a deep learning approach. Here's a paper where they did that.