Tag Archive for 'GWAS'

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Setting the record straight

The current issue of Cell has some important correspondence in response to an essay published by Jon McClellan and Mary Claire King in April. Daniel covered the original piece and hosted a guest post from Kai Wang which detailed some of the more obvious flaws in their argument. Now, Wang and his colleagues from Philadelphia have published an official response in Cell, in parallel with a similar letter from Robert Klein and colleagues from New York. Accompanying these is a further reply from McClellan and King. Read on for an overview of three contentious statements made in the original piece, and the rebuttals to each.

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Why prediction is a risky business

(This is an extended version of a short piece written as part of a series organized by the excellent Mary Carmichael at Newsweek. Readers eager for more detail on the statistics behind risk prediction should read Kate’s excellent discussion posted yesterday.)

In 2003 Francis Collins, having just led the human genome project to completion, made a prediction: within ten years, “predictive genetic tests will exist for many common conditions” and “each of us can learn of our individual risks for future illness”. The deadline of his prophecy is fast approaching, but how close are we to realizing his vision of being able to get a read-out of disease risk from a person’s DNA?
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How to read a genome-wide association study

As any avid follower of genomics or medical genetics knows, genome-wide association studies (GWAS) have been the dominant tool used by complex disease genetics researchers in the last five years. There’s a very active debate in the field about whether GWAS have revolutionized our understanding of disease genetics or whether they were a waste of money for little tangible gain. No matter where you fall in that spectrum, however, you need only to browse the table of contents of any recent issue of Nature Genetics to see how ubiquitous they are. Since GWAS provide so much of the fodder for unzipping your genome, and in order to help you cut through the hype in the mainstream press coverage of GWAS, I’ve put together a quick primer on how to go straight to the original paper and decide for yourself whether it’s a landmark finding or a dud.

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