Pub Date : 2021-10-15DOI: 10.1007/s12561-021-09324-4
Long Wang, Fangzheng Xie, Yanxun Xu
{"title":"Simultaneous Learning the Dimension and Parameter of a Statistical Model with Big Data","authors":"Long Wang, Fangzheng Xie, Yanxun Xu","doi":"10.1007/s12561-021-09324-4","DOIUrl":"https://doi.org/10.1007/s12561-021-09324-4","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47383406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-08DOI: 10.1007/s12561-021-09325-3
D. Ghosh, M. Sabel
{"title":"A Weighted Sample Framework to Incorporate External Calculators for Risk Modeling","authors":"D. Ghosh, M. Sabel","doi":"10.1007/s12561-021-09325-3","DOIUrl":"https://doi.org/10.1007/s12561-021-09325-3","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49257052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-01DOI: 10.1007/s12561-021-09323-5
A. Monseur, B. Carlin, B. Boulanger, A. Seferian, L. Servais, Chris Freitag, L. Thielemans, Teresa Elena Virginie Ulrike Andrea Adele James J. Basil Gidaro Gargaun Chê Schara Gangfuß D’Amico Dowling , T. Gidaro, E. Gargaun, V. Chê, U. Schara, A. Gangfuss, A. D’Amico, J. Dowling, B. Darras, A. Daron, Arturo E. Hernandez, C. de Lattre, J. Arnal, Michèle Mayer, J. Cuisset, C. Vuillerot, S. Fontaine, R. Bellance, V. Biancalana, A. Buj-Bello, J. Hogrel, H. Landy, K. Amburgey, B. Andres, E. Bertini, R. Cardaş, S. Denis, Dominique Duchêne, V. Latournerie, Nacera Reguiba, E. Tsuchiya, C. Wallgren‐Pettersson
{"title":"Leveraging Natural History Data in One- and Two-Arm Hierarchical Bayesian Studies of Rare Disease Progression","authors":"A. Monseur, B. Carlin, B. Boulanger, A. Seferian, L. Servais, Chris Freitag, L. Thielemans, Teresa Elena Virginie Ulrike Andrea Adele James J. Basil Gidaro Gargaun Chê Schara Gangfuß D’Amico Dowling , T. Gidaro, E. Gargaun, V. Chê, U. Schara, A. Gangfuss, A. D’Amico, J. Dowling, B. Darras, A. Daron, Arturo E. Hernandez, C. de Lattre, J. Arnal, Michèle Mayer, J. Cuisset, C. Vuillerot, S. Fontaine, R. Bellance, V. Biancalana, A. Buj-Bello, J. Hogrel, H. Landy, K. Amburgey, B. Andres, E. Bertini, R. Cardaş, S. Denis, Dominique Duchêne, V. Latournerie, Nacera Reguiba, E. Tsuchiya, C. Wallgren‐Pettersson","doi":"10.1007/s12561-021-09323-5","DOIUrl":"https://doi.org/10.1007/s12561-021-09323-5","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42161032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-18DOI: 10.1007/s12561-021-09321-7
Weiying Yuan, Ming-Hui Chen, J. Zhong
{"title":"Flexible Conditional Borrowing Approaches for Leveraging Historical Data in the Bayesian Design of Superiority Trials","authors":"Weiying Yuan, Ming-Hui Chen, J. Zhong","doi":"10.1007/s12561-021-09321-7","DOIUrl":"https://doi.org/10.1007/s12561-021-09321-7","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46761465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-09DOI: 10.1007/s12561-023-09368-8
M. Meyer, Hao Cheng, K. Knutson
{"title":"Bayesian Analysis of Multivariate Matched Proportions with Sparse Response","authors":"M. Meyer, Hao Cheng, K. Knutson","doi":"10.1007/s12561-023-09368-8","DOIUrl":"https://doi.org/10.1007/s12561-023-09368-8","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48568588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01Epub Date: 2019-07-27DOI: 10.1007/s12561-019-09253-3
Haixiang Zhang, Jun Chen, Zhigang Li, Lei Liu
Mediation analysis has been commonly used to study the effect of an exposure on an outcome through a mediator. In this paper, we are interested in exploring the mediation mechanism of microbiome, whose special features make the analysis challenging. We consider the isometric logratio transformation of the relative abundance as the mediator variable. Then, we present a de-biased Lasso estimate for the mediator of interest and derive its standard error estimator, which can be used to develop a test procedure for the interested mediation effect. Extensive simulation studies are conducted to assess the performance of our method. We apply the proposed approach to test the mediation effect of human gut microbiome between the dietary fiber intake and body mass index.
{"title":"Testing for mediation effect with application to human microbiome data.","authors":"Haixiang Zhang, Jun Chen, Zhigang Li, Lei Liu","doi":"10.1007/s12561-019-09253-3","DOIUrl":"10.1007/s12561-019-09253-3","url":null,"abstract":"<p><p>Mediation analysis has been commonly used to study the effect of an exposure on an outcome through a mediator. In this paper, we are interested in exploring the mediation mechanism of microbiome, whose special features make the analysis challenging. We consider the isometric logratio transformation of the relative abundance as the mediator variable. Then, we present a de-biased Lasso estimate for the mediator of interest and derive its standard error estimator, which can be used to develop a test procedure for the interested mediation effect. Extensive simulation studies are conducted to assess the performance of our method. We apply the proposed approach to test the mediation effect of human gut microbiome between the dietary fiber intake and body mass index.</p>","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8177450/pdf/nihms-1578730.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38998807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1007/s12561-020-09294-z
Jing Ma
Joint analysis of microbiome and metabolomic data represents an imperative objective as the field moves beyond basic microbiome association studies and turns towards mechanistic and translational investigations. We present a censored Gaussian graphical model framework, where the metabolomic data are treated as continuous and the microbiome data as censored at zero, to identify direct interactions (defined as conditional dependence relationships) between microbial species and metabolites. Simulated examples show that our method metaMint performs favorably compared to the existing ones. metaMint also provides interpretable microbe-metabolite interactions when applied to a bacterial vaginosis data set. R implementation of metaMint is available on GitHub.
{"title":"Joint Microbial and Metabolomic Network Estimation with the Censored Gaussian Graphical Model.","authors":"Jing Ma","doi":"10.1007/s12561-020-09294-z","DOIUrl":"https://doi.org/10.1007/s12561-020-09294-z","url":null,"abstract":"<p><p>Joint analysis of microbiome and metabolomic data represents an imperative objective as the field moves beyond basic microbiome association studies and turns towards mechanistic and translational investigations. We present a censored Gaussian graphical model framework, where the metabolomic data are treated as continuous and the microbiome data as censored at zero, to identify direct interactions (defined as conditional dependence relationships) between microbial species and metabolites. Simulated examples show that our method metaMint performs favorably compared to the existing ones. metaMint also provides interpretable microbe-metabolite interactions when applied to a bacterial vaginosis data set. R implementation of metaMint is available on GitHub.</p>","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s12561-020-09294-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10743117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01Epub Date: 2021-03-27DOI: 10.1007/s12561-021-09306-6
Shaoyu Li, Yanqing Sun, Liyang Diao, Xue Wang
Non-standard structured, multivariate data are emerging in many research areas, including genetics and genomics, ecology, and social science. Suitably defined pairwise distance measures are commonly used in distance-based analysis to study the association between the variables. In this work, we consider a linear quantile regression model for pairwise distances. We investigate the large sample properties of an estimator of the unknown coefficients and propose statistical inference procedures correspondingly. Extensive simulations provide evidence of satisfactory finite sample properties of the proposed method. Finally, we applied the method to a microbiome association study to illustrate its utility.
{"title":"Distance-Based Analysis with Quantile Regression Models.","authors":"Shaoyu Li, Yanqing Sun, Liyang Diao, Xue Wang","doi":"10.1007/s12561-021-09306-6","DOIUrl":"https://doi.org/10.1007/s12561-021-09306-6","url":null,"abstract":"<p><p>Non-standard structured, multivariate data are emerging in many research areas, including genetics and genomics, ecology, and social science. Suitably defined pairwise distance measures are commonly used in distance-based analysis to study the association between the variables. In this work, we consider a linear quantile regression model for pairwise distances. We investigate the large sample properties of an estimator of the unknown coefficients and propose statistical inference procedures correspondingly. Extensive simulations provide evidence of satisfactory finite sample properties of the proposed method. Finally, we applied the method to a microbiome association study to illustrate its utility.</p>","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s12561-021-09306-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40601803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-15DOI: 10.1007/S12561-021-09310-W
Boyi Guo, H. Holscher, L. Auvil, M. Welge, C. Bushell, J. Novotny, D. Baer, N. Burd, Naiman A. Khan, Ruoqing Zhu
{"title":"Estimating Heterogeneous Treatment Effect on Multivariate Responses Using Random Forests","authors":"Boyi Guo, H. Holscher, L. Auvil, M. Welge, C. Bushell, J. Novotny, D. Baer, N. Burd, Naiman A. Khan, Ruoqing Zhu","doi":"10.1007/S12561-021-09310-W","DOIUrl":"https://doi.org/10.1007/S12561-021-09310-W","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/S12561-021-09310-W","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49077447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-12DOI: 10.1007/S12561-021-09308-4
Jinge Yu, Qiuyu Wu, Xiangyu Luo
{"title":"Bayesian Joint Modeling of Single-Cell Expression Data and Bulk Spatial Transcriptomic Data","authors":"Jinge Yu, Qiuyu Wu, Xiangyu Luo","doi":"10.1007/S12561-021-09308-4","DOIUrl":"https://doi.org/10.1007/S12561-021-09308-4","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/S12561-021-09308-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48166554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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