However, SNPs linked to disease account for only a minuscule fraction of the estimated 10 million SNPs found in the human genome. Scientists have made great strides to narrow down the genetic playfield to just the genetic variations that cause disease, but other minor genetic variations like ancestry are only recently being accounted for. With this study, researchers will be able to quickly and inexpensively identify the genes linked to ancestry and unrelated to disease, and remove many of them from contention as causes of disease, thus greatly narrowing the search.
With this method, the researchers did not need prior information from the participants regarding their ancestry, which is required for most current genetic population studies. "Because this method is purely computational and leverages linear algebraic methods such as Principal Components Analysis, without the use of information on self-reported ancestry, we were able to treat the data as a black box," Drineas said. Drineas does note that such self-reporting in genetics studies remains a fairly accurate and important way to trace ancestry, but is often difficult in populations as varied as European Americans.
The European American population was chosen because its genetic background, reflecting its historic origins, is among the most complex on the planet, requiring fine resolution characterization of the genetic code in order to define genetic structure, according to Drineas.
The researchers analyzed 1,521 individuals for more than 300,000 SNPs across the entire genome. The data were made available by the National Instit
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| Contact: Gabrielle DeMarco demarg@rpi.edu 518-276-6542 Rensselaer Polytechnic Institute Source:Eurekalert |