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Miranda Lynch

University of Connecticut Health Center



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Jessica M. Clement

University of Connecticut Neag Comprehensive Cancer Center



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429 – Methods for Next-Generation Sequencing and -Omics Data

Bayesian Functional Data Methods in Copy Number Alteration Studies: Applications in Urothelial Bladder Carcinoma

Sponsor: Biometrics Section
Keywords: functional data regression, bladder cancer, copy number alterations, Bayesian inference

Miranda Lynch

University of Connecticut Health Center

Jessica M. Clement

University of Connecticut Neag Comprehensive Cancer Center

Chromosomal level alterations in the genome are a hallmark of cancer, and methods to probe copy number alterations (CNAs) have revealed a number of important drivers of oncogenesis and tumor progression. This work is motivated by our research questions in urothelial bladder carcinoma (BLCA), investigating the interconnections between smoking status/history and immune response in BLCA progression. In this work, copy number profiles are characterized using Bayesian functional data methods employing wavelet basis functions. These basis functions are well suited for the types of profiles that appear in copy number studies using array CGH and SNP arrays. We propose methods using these profiles for functional regression to examine the relationship to smoking and to look at whether the altered genomic regions preferentially include genes indicative of immune response. We apply our methods to publicly available bladder cancer data from a group of patients with metastatic disease.

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