In this workshop, we will focus on the PCSK9 gene and its connection to LDL levels for participants in the All of Us database.
Using Electronic Health Record (EHR) data and provided genomic information, we will showcase a comprehensive approach that encompasses data cleaning and filtering to isolate specific genomic regions of interest. In addition to these preparatory steps, we will conduct a logistic regression analysis, utilizing disease status as the outcome variable and a single genetic variant as the predictor. These analytical skills serve as a solid foundation for future genome-wide association studies (GWAS) and provide a crucial resource for researchers.
Target Audience: Researchers interested in the application of statistical methods to biological, genetic, and health-related data.
- Create a cohort of individuals with Whole Genome Sequencing and LDL measurements using the Cohort Builder.
- Import variables from various All of Us domains into a Jupyter notebook using the Dataset Builder.
- Execute data cleaning procedures on phenotype data from Person, Measurement, Observation, Survey and Drug domains.
- Filter genomic data to isolate specific variants in PCSK9 gene and perform quality assessments.
- Combine genomic data effectively with phenotype data and carry out summary statistics.
- Conduct linear regression analyses, both unadjusted and adjusted.
- Completion of Controlled Tier Training in the All of Us Researcher Workbench.
- Either attended the 'Introduction to All of Us Researcher Workbench' workshop or watched the corresponding workshop video for initial understanding and overview.