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BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data
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 fromdoi:10.1093/bioinformatics/btl089 pmid:16533818 fatcat:i4kimo7ph5cvjauys2a7je2dwy