MZINBVA: variational approximation for multilevel zero-inflated negative-binomial models for association analysis in microbiome surveys.

Liu, Tiantian; Xu, Peirong; Du, Yueyao; Lu, Hui; Zhao, Hongyu; Wang, Tao

Liu, Tiantian; Xu, Peirong; Du, Yueyao; Lu, Hui; Zhao, Hongyu; Wang, Tao.

Afiliação

Liu T; SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, 800 Dongchuan RD, 200240, Shanghai, China.
Xu P; Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200127, Shanghai, China.
Du Y; Department of Biostatistics, Yale University, 60 College Stree, CT 06520, New Haven, USA.
Lu H; MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, 800 Dongchuan RD, 200240, Shanghai, China.
Zhao H; SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, 800 Dongchuan RD, 200240, Shanghai, China.
Wang T; Department of Biostatistics, Yale University, 60 College Stree, CT 06520, New Haven, USA.

Brief Bioinform ; 23(1)2022 01 17.

Article em En | MEDLINE | ID: mdl-34718406

Assuntos

Microbiota; Simulação por Computador; Humanos; Modelos Estatísticos; Projetos de Pesquisa

Palavras-chave

GLMMs; differential abundance analysis; longitudinal and multilevel data; sandwich variance estimator; variational inference

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microbiota Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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