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Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ).
Ling, Wodan; Zhao, Ni; Plantinga, Anna M; Launer, Lenore J; Fodor, Anthony A; Meyer, Katie A; Wu, Michael C.
  • Ling W; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, 98109, USA.
  • Zhao N; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, 21205, USA.
  • Plantinga AM; Department of Mathematics and Statistics, Williams College, 18 Hoxsey St., Williamstown, 01267, USA.
  • Launer LJ; Laboratory of Epidemiology and Population Science, NIA, NIH, 7201 Wisconsin Ave, Bethesda, 20814, USA.
  • Fodor AA; Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, 28223, USA.
  • Meyer KA; Nutrition Research Institute and Department of Nutrition, University of North Carolina, 500 Laureate Way, Kannapolis, 28081, USA.
  • Wu MC; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, 98109, USA. mcwu@fredhutch.org.
Microbiome ; 9(1): 181, 2021 09 02.
Article en En | MEDLINE | ID: mdl-34474689
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Microbiota Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2021 Tipo del documento: Article
Texto completo
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PubMed Links
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Microbiota Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2021 Tipo del documento: Article