Analysis of genomic variants for investigating the genetic etiology of disease [electronic resource]
- Daniel Edmund Newburger.
- Physical description
- 1 online resource.
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|3781 2015 N||In-library use|
- Newburger, Daniel Edmund.
- Batzoglou, Serafim, primary advisor.
- Pritchard, Jonathan D., advisor.
- Sidow, Arend, advisor.
- Stanford University. Department of Biomedical Informatics.
- The study of genomic variation within human populations is critical for elucidating the genetic factors that contribute to disease. Identifying and characterizing the genetic architecture of disease advances clinical care by facilitating the development of novel diagnostic tools, the identification of new therapeutic targets, and the practice of personalized treatment for genetic syndromes. The massive volume of genetic data generated by modern genotyping technologies, combined with the informatics challenges of filtering and interpreting these noisy measurements, represent significant obstacles to genomic research. These technical issues necessitate the development of computationally efficient methodologies that leverage raw genotype data for the comparative genomic analysis of complex phenotypes across human subpopulations. In this dissertation, I describe my contributions towards the biomedical study of genetic syndromes using high-throughput genotyping technologies. First, I discuss methods for studying the genome evolution of pre-malignant cancer lesions during progression to breast cancer. Second, I describe algorithms for performing highly accurate variant validation in genomic studies using next generation sequencing. Finally, I present methods for identifying novel disease susceptibility loci in complex diseases using identity by descent mapping in large case-control cohorts.
- Publication date
- Submitted to the Department of Biomedical Informatics.
- Thesis (Ph.D.)--Stanford University, 2015.
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