Lucas Ueta
Undergraduate Student, University of California, Irvine
2 active projects
Prostate Cancer SNP Analysis
Scientific Questions Being Studied
Prostate cancer is a significant burden to Black American (BA) men as compared to White Americans with European heritage (WA). We have identified a difference between races in human endogenous retroviral elements (ERVs) that may be responsible, at least in part, for this worse outcome. Studies have found that BAs with prostate cancer have a higher frequency of several germline risk single-nucleotide polymorphisms (SNPs) compared to their WA counterparts. The goal of the proposed study here is to utilize genomic data from AoU to explore the link between ERVs and germline disease variants in both cohorts (i.e., BA and WA PCa patients).
Project Purpose(s)
- Disease Focused Research (prostate cancer)
Scientific Approaches
We will use the genome sequencing (WGS) data from prostate cancer patients to identify ERVs that are located in the vicinity of high-risk SNPs and determine if they differ between patients of different ancestries. In prior published work, we have created a novel bioinformatic mapping pipeline for ERV analysis and have applied this tool to study multiple diseases including PCa, cervical cancer, and Alzheimer disease. This platform can be adapted to investigate the link between ERVs and the high-risk SNPs in PCa patients of different races.
Anticipated Findings
The link between ERVs and germline disease variants is not well understood. Our initial analysis identified several ERVs with prognostic potential in prostate cancer that are in close vicinity to SNPs associated with prostate cancer risk. The proposed study extends our understanding of the potential relationships between ERVs, genetic variations, and disease risk/prognosis.
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Controlled TierResearch Team
Owner:
- Lucas Ueta - Undergraduate Student, University of California, Irvine
- Nicholas Korvink - Undergraduate Student, University of California, Irvine
- Farah Rahmatpanah - Senior Researcher, University of California, Irvine
Duplicate of Beginner Intro to AoU Data and the Workbench (v7)
Scientific Questions Being Studied
This workspace contains multiple notebooks that assess users' understanding of the workbench and OMOP. These notebooks are meant to help users check their knowledge not only on Python, R, and SQL, but also on the general data structure and data model used by the All of Us program.
Project Purpose(s)
- Educational
Scientific Approaches
There are no scientific approach used in this workspace because it is meant for educational purposes only. We will cover all aspects of OMOP, and hence will use most datasets available in the workbench.
Anticipated Findings
We do not anticipate to have any findings. Instead, we are educating people on the use of the workbench and the common data model OMOP used by the program.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierRequest a Review of this Research Project
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