Publications by authors named "Julia Gimbernat-Mayol"
We analyze dog genotypes (i.e., positions of dog DNA sequences that often vary between different dogs) in order to predict the corresponding phenotypes (i.
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- The study presents Archetypal Analysis as a more efficient and unsupervised method for estimating genetic clusters in genomic data, making it particularly useful for large and diverse cohorts.
- Unlike traditional methods like ADMIXTURE that require extensive computational resources, Archetypal Analysis significantly reduces compute time and memory usage, allowing for faster analysis of genetic data.
- The findings suggest that Archetypal Analysis not only produces similar cluster structures as existing methods but also helps avoid misinterpretations related to socially constructed ethnic labels in genetics.