Li, Xihao; Li, Zilin; Zhou, Hufeng; Gaynor, Sheila M; Liu, Yaowu; Chen, Han; Sun, Ryan; Dey, Rounak; Arnett, Donna K.; Sabino, Ester Cerdeira 
Source: Nature genetics. Unidade: FM
Subjects: COLESTEROL, PREDISPOSIÇÃO GENÉTICA PARA DOENÇA, VARIAÇÃO GENÉTICA, GENOMAS, FENÓTIPOS
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LI, Xihao et al. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nature genetics, v. 52, n. 9, p. 969-+, 2020Tradução . . Disponível em: https://doi.org/10.1038/s41588-020-0676-4. Acesso em: 10 nov. 2024.APA
Li, X., Li, Z., Zhou, H., Gaynor, S. M., Liu, Y., Chen, H., et al. (2020). Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nature genetics, 52( 9), 969-+. doi:10.1038/s41588-020-0676-4NLM
Li X, Li Z, Zhou H, Gaynor SM, Liu Y, Chen H, Sun R, Dey R, Arnett DK, Sabino EC. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale [Internet]. Nature genetics. 2020 ; 52( 9): 969-+.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1038/s41588-020-0676-4Vancouver
Li X, Li Z, Zhou H, Gaynor SM, Liu Y, Chen H, Sun R, Dey R, Arnett DK, Sabino EC. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale [Internet]. Nature genetics. 2020 ; 52( 9): 969-+.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1038/s41588-020-0676-4
