> Right now I cannot benefit from [cheap gene sequencing] in everyday hospital. I work in a lab with people who are working on developing diagnostics for trans

> Right now I cannot benefit from [cheap gene sequencing] in everyday hospital. I work in a lab with people who are working on developing diagnostics for transplant rejection based on sequencing the RNA from a small sample of your blood and using a trained machine learning classifier to diagnose rejection (I'm tangentially involved in this project). It's still a ways away from clinical application, but if successful, it could replace the current gold standard for diagnosis, which is an invasive biopsy of the graft that is then manually inspected under a microscope by a trained histologist. That's a pretty big step up, from a biopsy and a histologist to a few drops of blood and a computer classifier to diagnose transplant rejection with the same accuracy. It would mean that you could monitor for signs of rejection much more often because drawing blood is much less invasive. This, in turn, would allow you to detect rejection events much earlier and take action to control the inflammation and prevent loss of the graft before it's too late. There's huge potential for quality-of-life improvements here. And I can assure you many other labs are applying the same methods to all sorts of diagnostic problems, not just transplant rejection. I could imagine a future where we have hundreds of trained classifiers for all sorts of diseases based on blood gene expression, and as a routine part of a doctor's visit, your blood will be drawn, sequenced in a matter of minutes, and run through all of these classifiers to identify any diseases you might possibly have, which can then be tested for by more accurate conventional tests now that the doctor knows what to test for. Here's the paper I was involved in: http://www.ncbi.nlm.nih.gov/pubmed/24725967 http://www.ncbi.nlm.nih.gov/pubmed/24725967 Here's a similar earlier paper that will also give you the idea of what we're up to and that I think is public access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2041877/ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2041877/