Identify elements of women’s omics profiles associated with menopausal status and time since menopause
Marisa Medina, Professor
UC San Francisco
Closed. This professor is continuing with Fall 2024 apprentices on this project; no new apprentices needed for Spring 2025.
There are a limited number of human omics datasets that include menopausal status information for female subjects and include enough premenopausal and postmenopausal women. For instance, multi-omics data has been generated for thousands of Framingham Heart Study (FHS) participants and hundreds of TwinsUK female twin pairs. We will compare transcriptomic, proteomic, and metabolomic profiles of premenopausal and postmenopausal women from these and other available studies and will identify genes, proteins, and metabolites that differ by menopausal status and/or are correlated with time since menopause in postmenopausal women.
Role: 1) The undergraduate would learn about human subjects research and be trained to protect human subjects before analyzing human subjects data.
2) Under direction of the research supervisor, the undergraduate would curate downloaded datasets from Framingham Heart Study, TwinsUK, and other sources, generating descriptive statistics and performing quality control to arrive at a final dataset for analysis.
3) The undergraduate would learn and/or expand their knowledge of omics data types, including transcriptomic, metabolomic, and proteomic data.
4) Under direction of the research supervisor, the undergraduate would statistically compare omics profiles from women of different menopause status, ideally identifying genes and pathways that are differentially regulated in premenopausal versus postmenopausal women.
Qualifications: An interest and some basic experience with statistics and coding would be a good foundation for this project.
A motivated student with a desire to analyze datasets that are relevant to human (women's) health would be ideal.
It would be desirable but not essential for the student to have prior experience analyzing some sort of omics dataset and/or have proficiency in at least one programming language.
Day-to-day supervisor for this project: Beth Theusch, Staff Researcher
Hours: to be negotiated
Off-Campus Research Site: This is a data analysis project, so project can be conducted completely remotely. The Medina lab is physically located at 5700 Martin Luther King Jr Way in Oakland, but the research supervisor works remotely.
Related website: https://profiles.ucsf.edu/elizabeth.theusch
Related website: https://medinalab.ucsf.edu/