Over the years I have submitted my share of failed grant proposals. Indeed, at the risk of immodesty, I would put my ability to fail to get external funding right up there with anybody’s. The pain comes not so much from the knowledge that I am not worthy in the eyes of my peers, or even from the score the reviewers have given me, which describes in a single succinct and “objective” term the epicness of my fail (<cough> 62 <cough>). Rather, it is in having to read the reviews and confront the exact nature of why this particular piece of work is such a steaming pile of poo.
Sometimes this process can be edifying, humbling, character-building, etc. “What doesn’t kill me makes me stronger.” “I will learn from my mistakes and do better next time.” But other times it’s merely aggravating: if the reviewers have not understood what it is you’re proposing and are criticizing you for something that is actually nowhere to be found in your grant application: if, for example, you shot the sheriff, but they want to bring you in guilty for the killing of a deputy.
It is this fear above all else that I bring to the prospect of reading reviews of my book. Not that reviewers will hate me or hate the book. It’s that they won’t get it. Which is why it’s so gratifying to read a review–in The Lancet, of all places–written by a reviewer who not only appreciates what I am trying to do, but completely and utterly gets it:
While it’s easy to visualise a world of personalised health care, even with tools available today, what is significantly less clear is how to get from here to there. How for example do we deal with error? (A zero cost genome is no good if the error checking costs are $10 000.) And although the role of multiple small effect variants remains uncertain, and certainly untested, as a tool for personalised risk prediction, whole genome sequencing will likely revolutionise the diagnosis and management of the many families affected by Mendelian disease. As a community, we need to start preparing for how to understand and leverage whole genome information across families.
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