Hidden Markov models approach to the analysis of array CGH data

Abstract

The development of solid tumors is associated with acquisition of complex genetic alterations, indicating that failures in the mechanisms that maintain the integrity of the genome contribute to tumor evolution. Thus, one expects that the particular types of genomic alterations seen in tumors reflect underlying failures in maintenance of genetic stability, as well as selection for changes that provide growth advantage. In order to investigate genomic alterations we are using microarray-based comparative genomic hybridization (array CGH). The computational task is to map and characterize the number and types of copy number alterations present in the tumors, and so define copy number phenotypes and associate them with known biological markers.To utilize the spatial coherence between nearby clones, we use an unsupervised hidden Markov models approach. The clones are partitioned into the states which represent the underlying copy number of the group of clones. The method is demonstrated on the two cell line datasets, one with known copy number alterations. The biological conclusions drawn from the analyses are discussed. r 2004 Elsevier Inc. All rights reserved.

Rare amplicons implicate frequent deregulation of cell fate specification pathways in oral squamous cell carcinoma

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Inferring copy number and genotype in tumour exome data

“…Previously, such data has been generated from array comparative genomic hybridisation (aCGH) and single nucleotide polymorphism (SNP) genotyping arrays [3–5] but the implementation of massively parallel sequencing (MPS) technologies has provided novel opportunities for using sequencing data to generate equivalent genomic aberration information. In the cancer genomics field it has become a routine to perform whole genome sequencing (WGS) or whole exome sequencing (WES) on DNA extracted from tumour tissues [2, 6, 7].…”

Uncover Cancer Genomics by Jointly Analysing Aneuploidy and Gene Expression

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