<p> With advances in genome sequencing technology, datasets with large sample sizes can be generated relatively quickly and cheaply, especially compared to the past decade or so. We can utilize this data to analyze the associations between genetic variants and gene expression, and how that in turn relates to specific phenotypes. We will explore the impact of structural variants (SVs) on gene expression and microRNA expression in healthy individuals. This dissertation is an application of expression quantitative trait loci (eQTL) analysis techniques on several of these datasets, as well as a description of an eQTL analysis pipeline software package.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10979471 |
| Date | 28 November 2018 |
| Creators | Quitadamo, Andrew |
| Publisher | The University of North Carolina at Charlotte |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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