These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
403 related articles for article (PubMed ID: 27187200)
21. Compositional zero-inflated network estimation for microbiome data. Ha MJ; Kim J; Galloway-Peña J; Do KA; Peterson CB BMC Bioinformatics; 2020 Dec; 21(Suppl 21):581. PubMed ID: 33371887 [TBL] [Abstract][Full Text] [Related]
22. Bayesian variable selection for multivariate zero-inflated models: Application to microbiome count data. Lee KH; Coull BA; Moscicki AB; Paster BJ; Starr JR Biostatistics; 2020 Jul; 21(3):499-517. PubMed ID: 30590511 [TBL] [Abstract][Full Text] [Related]
23. Negative Binomial Mixed Models for Analyzing Longitudinal Microbiome Data. Zhang X; Pei YF; Zhang L; Guo B; Pendegraft AH; Zhuang W; Yi N Front Microbiol; 2018; 9():1683. PubMed ID: 30093893 [TBL] [Abstract][Full Text] [Related]
24. Correlation and association analyses in microbiome study integrating multiomics in health and disease. Xia Y Prog Mol Biol Transl Sci; 2020; 171():309-491. PubMed ID: 32475527 [TBL] [Abstract][Full Text] [Related]
25. Compositional knockoff filter for high-dimensional regression analysis of microbiome data. Srinivasan A; Xue L; Zhan X Biometrics; 2021 Sep; 77(3):984-995. PubMed ID: 32683674 [TBL] [Abstract][Full Text] [Related]
26. Compositional data analysis of the microbiome: fundamentals, tools, and challenges. Tsilimigras MC; Fodor AA Ann Epidemiol; 2016 May; 26(5):330-5. PubMed ID: 27255738 [TBL] [Abstract][Full Text] [Related]
27. A Zero-Inflated Latent Dirichlet Allocation Model for Microbiome Studies. Deek RA; Li H Front Genet; 2020; 11():602594. PubMed ID: 33552122 [TBL] [Abstract][Full Text] [Related]
28. Generalized Hotelling's test for paired compositional data with application to human microbiome studies. Zhao N; Zhan X; Guthrie KA; Mitchell CM; Larson J Genet Epidemiol; 2018 Jul; 42(5):459-469. PubMed ID: 29737047 [TBL] [Abstract][Full Text] [Related]
29. coda4microbiome: compositional data analysis for microbiome cross-sectional and longitudinal studies. Calle ML; Pujolassos M; Susin A BMC Bioinformatics; 2023 Mar; 24(1):82. PubMed ID: 36879227 [TBL] [Abstract][Full Text] [Related]
30. A compositional mediation model for a binary outcome: Application to microbiome studies. Sohn MB; Lu J; Li H Bioinformatics; 2021 Dec; 38(1):16-21. PubMed ID: 34415327 [TBL] [Abstract][Full Text] [Related]
31. Multiscale adaptive differential abundance analysis in microbial compositional data. Wang S Bioinformatics; 2023 Apr; 39(4):. PubMed ID: 37018137 [TBL] [Abstract][Full Text] [Related]
33. Zero is not absence: censoring-based differential abundance analysis for microbiome data. Chan LS; Li G Bioinformatics; 2024 Feb; 40(2):. PubMed ID: 38331411 [TBL] [Abstract][Full Text] [Related]
34. mbDecoda: a debiased approach to compositional data analysis for microbiome surveys. Zong Y; Zhao H; Wang T Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38701410 [TBL] [Abstract][Full Text] [Related]
35. An adaptive direction-assisted test for microbiome compositional data. Zhang W; Liu A; Zhang Z; Chen G; Li Q Bioinformatics; 2022 Jul; 38(14):3493-3500. PubMed ID: 35640978 [TBL] [Abstract][Full Text] [Related]
36. HARMONIES: A Hybrid Approach for Microbiome Networks Inference via Exploiting Sparsity. Jiang S; Xiao G; Koh AY; Chen Y; Yao B; Li Q; Zhan X Front Genet; 2020; 11():445. PubMed ID: 32582274 [TBL] [Abstract][Full Text] [Related]
37. A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data. Jiang S; Xiao G; Koh AY; Kim J; Li Q; Zhan X Biostatistics; 2021 Jul; 22(3):522-540. PubMed ID: 31844880 [TBL] [Abstract][Full Text] [Related]
38. Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ). Ling W; Zhao N; Plantinga AM; Launer LJ; Fodor AA; Meyer KA; Wu MC Microbiome; 2021 Sep; 9(1):181. PubMed ID: 34474689 [TBL] [Abstract][Full Text] [Related]