BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data. Summary: We have developed a new method (BioHMM) for segmenting array comparative genomic hybridization data into states with the same underlying copy number. By utilizing a heterogeneous hidden Markov model, BioHMM incorporates relevant biological factors (e.g. the distance between adjacent clones) in the segmentation process. Availability: BioHMM is available as part of the R library snapCGH which can be downloaded from Supplementary information: Supplementary information is available at

References in zbMATH (referenced in 13 articles )

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  1. Cassese, Alberto; Guindani, Michele; Tadesse, Mahlet G.; Falciani, Francesco; Vannucci, Marina: A hierarchical Bayesian model for inference of copy number variants and their association to gene expression (2014)
  2. Luong, The Minh; Rozenholc, Yves; Nuel, Gregory: Fast estimation of posterior probabilities in change-point analysis through a constrained hidden Markov model (2013)
  3. Mayrink, Vinicius Diniz; Lucas, Joseph Edward: Sparse latent factor models with interactions: analysis of gene expression data (2013)
  4. Rueda, Oscar M.; Rueda, Cristina; Diaz-Uriarte, Ramon: A Bayesian HMM with random effects and an unknown number of states for DNA copy number analysis (2013)
  5. Yau, Christopher; Holmes, Christopher C.: A decision-theoretic approach for segmental classification (2013)
  6. Love, Michael I.; Myšičková, Alena; Sun, Ruping; Kalscheuer, Vera; Vingron, Martin; Haas, Stefan A.: Modeling read counts for CNV detection in exome sequencing data (2011)
  7. Magi, Alberto; Benelli, Matteo; Marseglia, Giuseppina; Nannetti, Genni; Scordo, Maria Rosaria: A shifting level model algorithm that identifies aberrations in array-CGH data (2010)
  8. Tai, Yu Chuan; Kvale, Mark N.; Witte, John S.: Segmentation and estimation for SNP microarrays: A Bayesian multiple change-point approach (2010)
  9. Desantis, Stacia M.; Houseman, E. Andrés; Coull, Brent A.; Louis, David N.; Mohapatra, Gayatry; Betensky, Rebecca A.: A latent class model with hidden Markov dependence for array CGH data (2009)
  10. Rancoita, Paola M. V.; Hutter, Marcus; Bertoni, Francesco; Kwee, Ivo: Bayesian DNA copy number analysis (2009) ioport
  11. Stjernqvist, Susann; Rydén, Tobias: A continuous-index hidden Markov jump process for modeling DNA copy number data (2009)
  12. Rueda, Oscar M.; Diaz-Uriarte, Ramon: A response to yu et al. ’A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array’, BMC bioinformatics 2007, 8: 145 (2007) ioport
  13. Marioni, J. C.; Thorne, N. P.; Tavaré, S.: Biohmm: A heterogeneous hidden Markov model for segmenting array cgh data (2006) ioport