Approaches for the functional interpretation of rare genetic variation
Abstract/Contents
- Abstract
- Rare variants, due to their abundance and often relatively recent appearance, are expected to play a large role in genetic contributions to disease. However, determining rare variants with potential to impact the development of rare or common diseases remains a challenge. In this dissertation, I discuss several projects assessing multi-omics data integration to identify functional rare variation and connect variants to both rare and common disease. In chapter 2, I present work analyzing transcriptomic data to improve rare disease diagnosis and in particular, identifying patterns of allele-specific expression in rare disease individuals that highlight genes associated with the patient's phenotype. In chapter 3, I present approaches using transcriptomes across ~50 tissues for ~800 individuals with matched whole genome sequencing to characterize rare variation leading to multitissue changes in gene expression, allelic imbalance and alternative splicing, a subset of which show strong associations with common diseases in an external cohort. In chapter 4, I assess additional functional signals, DNA methylation and plasma proteome abundance, in addition to transcriptomic information to further refine our understanding of how rare variants can contribute to downstream phenotypes, and identify rare variation contributing to large changes across DNA methylation, gene expression, and protein abundance in a multi-ethnic cohort. Together, this work provides several approaches for integrating functional multi-omics data into rare variant interpretation pipelines and evaluates their use across multiple contexts.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Ferraro, Nicole |
|---|---|
| Degree supervisor | Montgomery, Stephen, 1979- |
| Thesis advisor | Montgomery, Stephen, 1979- |
| Thesis advisor | He, Zihuai |
| Thesis advisor | Pritchard, Jonathan D |
| Thesis advisor | Sabatti, Chiara |
| Degree committee member | He, Zihuai |
| Degree committee member | Pritchard, Jonathan D |
| Degree committee member | Sabatti, Chiara |
| Associated with | Stanford University, Department of Biomedical Informatics |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Nicole M. Ferraro. |
|---|---|
| Note | Submitted to the Department of Biomedical Informatics. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/gr565vm0306 |
Access conditions
- Copyright
- © 2021 by Nicole Ferraro
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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