| Year |
Citation |
Score |
| 2017 |
Xu L, Paterson AD, Xu W. Bayesian latent variable models for hierarchical clustered count outcomes with repeated measures in microbiome studies. Genetic Epidemiology. PMID 28111783 DOI: 10.1002/Gepi.22031 |
0.404 |
|
| 2016 |
Xu L, Craiu RV, Sun L, Paterson AD. Parameter Expanded Algorithms for Bayesian Latent Variable Modeling of Genetic Pleiotropy Data. Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America. 25: 405-425. PMID 27752219 DOI: 10.1080/10618600.2014.988337 |
0.646 |
|
| 2016 |
Turpin W, Espin-Garcia O, Xu W, Silverberg MS, Kevans D, Smith MI, Guttman DS, Griffiths A, Panaccione R, Otley A, Xu L, Shestopaloff K, Moreno-Hagelsieb G, Paterson AD, et al. Association of host genome with intestinal microbial composition in a large healthy cohort. Nature Genetics. PMID 27694960 DOI: 10.1038/Ng.3693 |
0.303 |
|
| 2016 |
Xu L, Craiu RV, Sun L, Paterson AD. Parameter Expanded Algorithms for Bayesian Latent Variable Modeling of Genetic Pleiotropy Data Journal of Computational and Graphical Statistics. 25: 405-425. DOI: 10.1080/10618600.2014.988337 |
0.648 |
|
| 2015 |
Xu L, Paterson AD, Turpin W, Xu W. Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data. Plos One. 10: e0129606. PMID 26148172 DOI: 10.1371/Journal.Pone.0129606 |
0.389 |
|
| 2014 |
Xu L, Craiu RV, Derkach A, Paterson AD, Sun L. Using a Bayesian latent variable approach to detect pleiotropy in the Genetic Analysis Workshop 18 data. Bmc Proceedings. 8: S77. PMID 25519405 DOI: 10.1186/1753-6561-8-S1-S77 |
0.593 |
|
| 2011 |
Xu L, Craiu RV, Sun L. Bayesian methods to overcome the winner's curse in genetic studies Annals of Applied Statistics. 5: 201-231. DOI: 10.1214/10-Aoas373 |
0.624 |
|
| Show low-probability matches. |