A new method for sifting through genomic data has been developed by the researchers at the Brown University. The sifting is done with the intent to find genetic variants that have assisted populations in adapting to a given vicinity. The process has been referred as SWIF(r) and it can fit different statistical tests into a single umbrella of analysis. This arrangement of tests can then be employed to find the adaptability of genomes and the individual mutations. Until now, the individual statistical tests were used for genetic studies but they didn’t render any substantial results on their own. However, the new method combines all of these tests together to ease genetic study and interpretation.
Studying ‘Selective Sweep’ of Mutations
In humans and animals, the mutation of genomes is not characterized by any wayward combinations that could aid or obstruct human survival. However, certain mutations can be unique and may amplify the chances of survival for an organism or aid their reproductive ability. These mutations may trickle down to the progeny causing a ‘selective sweep’. The SWIF(r) intends to study these unique mutations in order to find the statistical signatures of selective sweeps. Although, this is not the only technique that uses multiple tests to study mutations, the correlations arising from these techniques are expected to be more useful than others.
Testing the Research Study
In order to practically employ their research hypothesis, the researchers studied a group of hunter-gatherers in South Africa. Since this group is often deprived of food supply, they have a higher chance of undergoing genetic predisposition. It would be interesting to see the impact of the study on global genetic sciences.