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Works (5)

Evaluation of polygenic scoring methods in five biobanks reveals greater variability between biobanks than between methods and highlights benefits of ensemble learning

2023-11-20 | Preprint
DOI: 10.1101/2023.11.20.23298215
Contributors: Remo Monti; Lisa Eick; Georgi Hudjashov; Kristi Läll; Stavroula Kanoni; Brooke N. Wolford; Benjamin Wingfield; Oliver Pain; Sophie Wharrie; Bradley Jermy et al.
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HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes

Bioinformatics
2023-09-02 | Journal article
DOI: 10.1093/bioinformatics/btad535
Contributors: Sophie Wharrie; Zhiyu Yang; Vishnu Raj; Remo Monti; Rahul Gupta; Ying Wang; Alicia Martin; Luke J O’Connor; Samuel Kaski; Pekka Marttinen et al.
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HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes

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2022-12-22 | Preprint | Author
DOI: 10.1101/2022.12.22.521552
Contributors: Sophie Wharrie; Zhiyu Yang; Vishnu Raj; Remo Monti; Rahul Gupta; Ying Wang; Alicia R. Martin; Luke O'Connor; Samuel Kaski; Pekka Marttinen et al.
Source: Self-asserted source
Sophie Wharrie
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Micro-, meso-, macroscales: The effect of triangles on communities in networks

Physical Review E
2019-08-21 | Journal article
DOI: 10.1103/physreve.100.022315
Part of ISSN: 2470-0045
Part of ISSN: 2470-0053
Source: Self-asserted source
Sophie Wharrie

HAPNEST: An efficient tool for generating large-scale genetics datasets from limited training data

NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research
Conference paper
Contributors: Wharrie, Sophie; Yang, Zhiyu; Raj, Vishnu; Monti, Remo; Gupta, Rahul; Wang, Ying; Martin, Alicia; O'Connor, Luke J; Kaski, Samuel; Marttinen, Pekka et al.
Source: Self-asserted source
Sophie Wharrie
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