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Predicting geographic location from genetic variation with deep neural networks
Most organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of known geographic origin. Here, we describe a deep le...
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| Publicado no: | eLife |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
eLife Sciences Publications, Ltd
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7324158/ https://ncbi.nlm.nih.gov/pubmed/32511092 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7554/eLife.54507 |
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