Lauryn Bruce

Graduate Trainee, University of California, San Diego

2 active projects

Personal and Family History of Cancer

As a demonstration project, we seek to understand family history characteristics in prevalence of cancer. Our questions are: 1. How does prevalence of cancer differ between those with and without family history of breast, colorectal, lung, ovarian and prostate cancer;…

Scientific Questions Being Studied

As a demonstration project, we seek to understand family history characteristics in prevalence of cancer. Our questions are: 1. How does prevalence of cancer differ between those with and without family history of breast, colorectal, lung, ovarian and prostate cancer; and 2) What, if any, differences exist by demographic characteristics.

Project Purpose(s)

  • Disease Focused Research (cancer)
  • Population Health
  • Other Purpose (This work is a result of an All of Us Research Program Demonstration Project. The projects are efforts by the Program designed to meet the program's goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. This work was reviewed and overseen by the All of Us Research Program Science Committee and the Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use.)

Scientific Approaches

We analyze all types of cancer in adults and compare analyses to published literature such as studies using SEER national cancer registry and national surveys such as National Health Information Survey. We identify cancer cases based on self-report from the PPI individual medical history survey. We identify family history of cancer from the PPI family medical history survey. We use Jupyter notebooks to generate reusable code.

Anticipated Findings

We anticipate that we will be able to replicate the relative prevalence and family history of cancer seen in the literature. This will serve to demonstrate the quality and utility of All of Us data and tools for conducting epidemiologic analyses.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation

Data Set Used

Registered Tier

Research Team

Owner:

  • Paulina Paul - Project Personnel, University of California, San Diego
  • Lauryn Bruce - Graduate Trainee, University of California, San Diego
  • Katherine Kim - Early Career Tenure-track Researcher, University of California, Davis
  • Jihoon Kim - Project Personnel, University of California, San Diego

Duplicate of AMIA Genomics Walkthrough

This workspace is intended to provide basic instruction for using genomics data in All of Us, including cohort identification, covariate extraction, analysis, and display of results. From AMIA 2021 conference

Scientific Questions Being Studied

This workspace is intended to provide basic instruction for using genomics data in All of Us, including cohort identification, covariate extraction, analysis, and display of results. From AMIA 2021 conference

Project Purpose(s)

  • Educational

Scientific Approaches

We use OMOP, the cohort builder, and Hail for genomics analysis. The approach will be a simple rule based algorithm along with some open access genomic data to simulate a GWAS.

Anticipated Findings

We do not anticipate any findings as the analysis will not be real. Therefore this will not contribute to scientific knowledge, but hopefully will contribute to individual user's knowledge.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Lauryn Bruce - Graduate Trainee, University of California, San Diego

Collaborators:

  • Jihoon Kim - Project Personnel, University of California, San Diego
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