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Showing 1–4 of 4 results
Advanced filters: Author: Arbel Harpak Clear advanced filters

  • Genetic predictors of health outcomes often drop in accuracy when applied to people dissimilar to participants of large genetic studies. Here, the authors investigate the root causes and highlight open questions underlying this problem.

    • Joyce Y. Wang
    • Neeka Lin
    • Arbel Harpak
    ResearchOpen Access
    Nature Communications
    Volume: 17, P: 1-10

  • CalPred is a framework that adjusts polygenic score (PGS) prediction intervals based on joint modeling of multiple contexts, such as age, sex and genetic ancestry. PGS show pervasive context-specific accuracy, suggesting that accounting for this will improve portability across contexts.

    • Kangcheng Hou
    • Ziqi Xu
    • Bogdan Pasaniuc
    Research
    Nature Genetics
    Volume: 56, P: 1386-1396

  • Christina Curtis and colleagues simulate spatial tumor growth under different evolutionary models and compare their results to multiregion sequencing data. They find that it is possible to distinguish tumors driven by strong positive selection from those evolving neutrally or under weak selection and infer different evolutionary modes within and between tumor types.

    • Ruping Sun
    • Zheng Hu
    • Christina Curtis
    Research
    Nature Genetics
    Volume: 49, P: 1015-1024