Analysis of Large-scale Alterations in Tumor Genomes
Brown University, Department of Computer Science & Center for Computational Molecular Biology
Cancer is a disease driven selection for somatic mutations that alter the structure, function or regulation of genes. These mutations range from single letter changes in DNA to rearrangements, gains, or losses of large pieces of DNA. In some types of cancer these large-scale alterations are directly implicated in cancer development and provide targets for cancer diagnostics and therapeutics.
The study of large-scale alterations in tumor genomes is presently exploding because the completion of the Human Genome Project has enabled high resolution analysis of tumor genomes. I will describe computational methods for analyzing rearrangements, duplications, and deletions in tumor genomes using a technique called End Sequence Profiling (ESP). These methods produce a parsimonious sequence of rearrangements that transform the normal human genome into a tumor genome. Computational analysis of ESP data suggests mechanisms that produce complicated patterns of overlapping rearrangement and duplication events that are observed in some tumor genomes. I will describe another experimental technique called array comparative genomic hybridization (aCGH) that has become indispensable in the identification of duplicated and deleted segments of DNA in tumor genomes. ESP provides an effective complement to aCGH, and I will discuss how to combine data from both types of experiments to obtain a comprehensive view of tumor genome architecture.
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