title: MRHMMs: multivariate regression hidden Markov models and the variantS.
abstract: CONCLUSIONS
  Hidden Markov models (HMMs) are flexible and widely used in scientific studies. Particularly in genomics and genetics, there are multiple distinct regimes in the genome within each of which the relationships among multivariate features are distinct. Examples include differential gene regulation depending on gene functions and experimental conditions, and varying combinatorial patterns of multiple transcription factors. We developed a software package called MRHMMs (Multivariate Regression Hidden Markov Models and the variantS) that accommodates a variety of HMMs that can be flexibly applied to many biological studies and beyond. MRHMMs supplements existing HMM software packages in two aspects. First, MRHMMs provides a diverse set of emission probability structures, including mixture of multivariate normal distributions and (logistic) regression models. Second, MRHMMs is computationally efficient for analyzing large data-sets generated in current genome-wide studies. Especially, the software is written in C for the speed advantage and further amenable to implement alternative models to meet users' own purposes.
  
  
  METHODS
  http://sourceforge.net/projects/mrhmms/
authors.affiliation: Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.
authors.forename: Yeonok
authors.initials: Y
authors.lastname: Lee
authors.affiliation: Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.
authors.forename: Debashis
authors.initials: D
authors.lastname: Ghosh
authors.affiliation: Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.
authors.forename: Ross C
authors.initials: RC
authors.lastname: Hardison
authors.affiliation: Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.
authors.forename: Yu
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D000818:Animals; D050982:GATA1 Transcription Factor / Q000378:metabolism; D016678:Genome; D023281:Genomics / Q000379:methods*; D016015:Logistic Models; D008390:Markov Chains; D051379:Mice; D015999:Multivariate Analysis; D016011:Normal Distribution; D012984:Software
chemical_list: D050982:GATA1 Transcription Factor; C494689:Gata1 protein, mouse