BDgraph swMATH ID: 14815 Software Authors: Mohammadi, A.; Wit, E.C. Description: Bayesian structure learning in sparse Gaussian graphical models. Decoding complex relationships among large numbers of variables with relatively few observations is one of the crucial issues in science. One approach to this problem is Gaussian graphical modeling, which describes conditional independence of variables through the presence or absence of edges in the underlying graph. In this paper, we introduce a novel and efficient Bayesian framework for Gaussian graphical model determination which is a trans-dimensional Markov Chain Monte Carlo (MCMC) approach based on a continuous-time birth-death process. We cover the theory and computational details of the method. It is easy to implement and computationally feasible for high-dimensional graphs. We show our method outperforms alternative Bayesian approaches in terms of convergence, mixing in the graph space and computing time. Unlike frequentist approaches, it gives a principled and, in practice, sensible approach for structure learning. We illustrate the efficiency of the method on a broad range of simulated data. We then apply the method on large-scale real applications from human and mammary gland gene expression studies to show its empirical usefulness. In addition, we implemented the method in the R package BDgraph which is freely available at url{http://CRAN.R-project.org/package=BDgraph}. Homepage: https://cran.r-project.org/web/packages/BDgraph/index.html Source Code: https://github.com/cran/BDgraph Keywords: Bayesian model selection; sparse Gaussian graphical models; non-decomposable graphs; birth-death process; Markov chain Monte Carlo; G-Wishart Related Software: R; glasso; huge; HdBCS; igraph; BGGM; Rcpp; bnlearn; qgraph; bfa; EMVS; openVA; ssgraph; ElemStatLearn; BayesianGLasso; BigQuic; glassoFast; cglasso; MASS (R); Monomvn Cited in: 19 Publications Standard Articles 1 Publication describing the Software Year BDgraph: An R Package for Bayesian Structure Learning in Graphical Models Mohammadi, A.; Wit, E.C. 2015 all top 5 Cited by 42 Authors 3 Ghosal, Subhashis 2 Li, Zehang Richard 2 Mohammadi, Reza 2 Mulgrave, Jami J. 2 Ni, Yang 2 Purutçuoğlu, Vilda 2 Waldorp, Lourens J. 1 Ağraz, Melih 1 Alexopoulos, Angelos 1 Ayyıldız, Ezgi 1 Baladandayuthapani, Veerabhadran 1 Beskos, Alexandros 1 Bottolo, Leonardo 1 Claeskens, Gerda 1 Clark, Samuel J. 1 Corander, Jukka 1 De Iorio, Maria 1 Dobra, Adrian 1 Huth, K. B. S. 1 Jahfari, Sara 1 Ji, Yuan 1 Kaptein, Maurits Clemens 1 Leppä-aho, Janne 1 Luo, Xiangyu 1 Marsman, Maarten 1 McComick, Tyler H. 1 McCormick, Tyler H. 1 Mohammadi, Abdolreza 1 Müller, Peter 1 Ntzoufras, Ioannis 1 Pensar, Johan 1 Pircalabelu, Eugen 1 Pratola, Matthew T. 1 Rhemtulla, Mijke 1 Roos, Teemu 1 Roy, Arkaprava 1 Stingo, Francesco Claudio 1 van den Boom, Willem 1 Vannucci, Marina 1 Weber, Gerhard-Wilhelm 1 Wit, Ernst C. 1 Wu, Qiuyu all top 5 Cited in 12 Serials 3 The Annals of Applied Statistics 3 Journal of Computational and Graphical Statistics 3 Bayesian Analysis 2 Psychometrika 1 Journal of the American Statistical Association 1 Journal of Multivariate Analysis 1 Journal of Statistical Planning and Inference 1 International Journal of Approximate Reasoning 1 European Journal of Operational Research 1 Journal of Statistical Computation and Simulation 1 Journal of Machine Learning Research (JMLR) 1 Statistical Methods and Applications all top 5 Cited in 8 Fields 18 Statistics (62-XX) 4 Biology and other natural sciences (92-XX) 3 Computer science (68-XX) 1 General and overarching topics; collections (00-XX) 1 Combinatorics (05-XX) 1 Probability theory and stochastic processes (60-XX) 1 Numerical analysis (65-XX) 1 Operations research, mathematical programming (90-XX) Citations by Year