Negative binomial mixed models for analyzing microbiome count data

BMC Bioinformatics

Volumn 18, Issue 1, 2017, Pages

  Zhang, Xinyan ^a   Mallick, Himel ^b,c   Tang, Zaixiang ^d   Zhang, Lei ^d   Cui, Xiangqin ^a   Benson, Andrew K ^e   Yi, Nengjun ^a  

^a UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^c BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^d MEDICAL COLLEGE OF SOOCHOW UNIVERSITY   (China)

^e UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Correlated measures; Count data; Metagenomics; Microbiome; Negative binomial model; Penalized Quasi likelihood; Random effects

Indexed keywords

DISPERSIONS; RANDOM PROCESSES;

CORRELATED MEASURES; COUNT DATUM; METAGENOMICS; MICROBIOME; NEGATIVE BINOMIAL MODELS; QUASI-LIKELIHOOD; RANDOM EFFECTS;

ITERATIVE METHODS;

ANIMAL EXPERIMENT; DISEASE SIMULATION; GASTROINTESTINAL TRACT; LEAST SQUARE ANALYSIS; METAGENOMICS; MICROBIOME; NONHUMAN; STATISTICAL MODEL; ALGORITHM; ANIMAL; BACTERIUM; C57BL MOUSE; CHEMISTRY; COMPUTER INTERFACE; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN; INTERNET; INTESTINE; MALE; METABOLISM; MICROBIOLOGY; MICROFLORA; MOUSE;

RNA 16S;

ALGORITHMS; ANIMALS; BACTERIA; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; INTERNET; INTESTINES; MALE; MICE; MICE, INBRED C57BL; MICROBIOTA; MODELS, STATISTICAL; RNA, RIBOSOMAL, 16S; USER-COMPUTER INTERFACE;

EID: 85008149994     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-1441-7     Document Type: Article

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