Accurate methods for ancestry and relatedness inference
- Jesse M. Rodriguez.
- Dec. 2013.
- Physical description
- online resource (xvi, 110 pages) : illustrations (some color)
- Rodriguez, Jesse M.
- Altman, Russ thesis advisor.
- Batzoglou, Serafim. thesis advisor (primary).
- Bustamante, Carlos (Carlos D.). thesis advisor.
- Stanford University. Program in Biomedical Informatics.
- Includes bibliographical references (p. 102-110). 62 refs.
- ["The predisposition to many diseases is strongly influenced by the genome of an individual. However, the association between the genome and most diseases is not fully understood, so there is an ongoing effort to characterize these associations. One way to characterize disease-genome associations is by studying the familial and ancestral origin of individuals in the context of disease. This kind of study relies on the fact that individuals with shared origins tend to have genomes and phenotypes that are similar to one another. Detailed information regarding familial and ancestral origin is often unknown, however, it can be inferred computationally by examining the genome. Therefore, it is important that we have accurate methods to infer this information in order to facilitate disease-genome associations. In this dissertation, I describe the contributions I have made to accurately inferring the ancestry and relatedness of individuals based on their genomes. First, I describe my work on ALLOY, a method to infer the ancestral origin of segments of the genome based on a factorial HMM. Next, I present PARENTE, a method to infer which individuals in a group are related to one another by detecting genomic segments that are identical-by-descent (IBD) using an embedded likelihood ratio test. Finally, I present PARENTE2, an extension of PARENTE that incorporates linkage disequilibrium information and results in significantly higher accuracy."]
- Publication date
- Submitted to the Program in Biomedical Informatics and the Committee on Graduate Studies of Stanford University.
- Thesis (Ph.D.)--Stanford University, 2013.