Writing in the journal Cell, a group of Stanford University geneticists write that such large studies are likely to produce genetic variants with little bearing on the disease in question-essentially false positives that confuse the results. Now, though, a new analysis calls the entire approach into question. Includes downloads, cheats, reviews, and articles. This thinking has resulted in an entire catalogue of hundreds of research studies that has shed light on the genetic origins of diseases such as type 2 diabetes, Parkinson’s disease, Crohn’s disease, and prostate cancer, while helping fuel the rise of personalized medicine. The logic here is simple: If you have a whole lot of people with a disease, you should be able to tell what genetic traits those people have in common that might be responsible. As both genetic sequencing has gotten cheaper and computerized data analysis has gotten better, more and more researchers have turned to what are known as genome- wide association studies in hopes of sussing out which individual genes are associated with particular disorders. The more data, the better, right? When it comes to genetics, it turns out that might not be the case. This Study is Forcing Scientists to Rethink the Human Genome.
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