Hidden Markov models approach to the analysis of array CGH data

摘要: The development of solid tumors is associated with acquisition complex genetic alterations, indicating that failures in the mechanisms maintain integrity genome contribute to tumor evolution. Thus, one expects particular types genomic alterations seen reflect underlying maintenance stability, as well selection for changes provide growth advantage. In order investigate we are using microarray-based comparative hybridization (array CGH). computational task map and characterize number copy alternations present tumors, so define phenotypes associate them known biological markers.To utilize spatial coherence between nearby clones. use an unsupervised hidden Markov models approach. clones partitioned into states which represent group method demonstrated on two cell line datasets, alterations. conclusions drawn from analyses discussed.