July 22–26 and July 29–August 2, 2024
[planning in progress - some details below are for 2023]
The 2024 CQS Summer Institute will include three in-person courses on the Vanderbilt University Medical Center campus, at 2525 West End Avenue, and one virtual course. Registration will open around May 6.
These great weeklong courses will sharpen your quantitative research skills and deepen your understanding of biostatistics and bioinformatics. Participants are highly encouraged to enroll in multiple courses.
TUITION per course (in USD)
Regular: $950
Vanderbilt University / Vanderbilt University Medical Center faculty and staff: $700
Vanderbilt University / Vanderbilt University Medical Center students, trainees, and postdocs: $450
ONLINE COURSE
Introduction to the All of Us Research Program
[dates and time TBA; course details are from 2023 and will be updated soon]
Course directors:
Paul Harris, PhD, professor of biomedical informatics, biomedical engineering, and biostatistics
Qingxia "Cindy" Chen, PhD, professor of biostatistics, biomedical informatics, and ophthalmology & visual sciences
The All of Us Research Program large-scale initiative that collects and studies data from over one million participants in the United States. This program gathers diverse data types, such as survey data, electronic health records, physical measurements, mobile health data (Fitbit), whole genome sequences, and array data. As a freely accessible resource, it plays a crucial role in improving health and advancing precision medicine. Researchers can access and analyze All of Us data via the Researcher Workbench, a secure Google cloud-based platform. This short course will cover (1) an overview of the Researcher Workbench and its built-in tools, (2) the process of identifying and extracting variables, and (3) case studies illustrating the analysis of various data types using the Workbench.
Prerequisites:
- Basic programming knowledge in R or Python.
- By the start of the course, you must have your All of Us researcher workbench account set up, with completion of the required training. To obtain an account, complete all the steps at researchallofus.org/register. Because of the multiple requirements to be met, including participation in an hour-long training session, we strongly advise initiating your account set-up by June 17 at the latest.
Note: The All of Us Research Program is currently available only to individuals at US-based academic, nonprofit, or health care institutions. Before registering for the course, please ensure your institution has an agreement on file, which can be found at the All of Us institutional agreements page. If your organization does not have an agreement, you can initiate one via the Institutional DURA Request form. If you encounter technical issues during registration, please contact support[at]researchallofus.org.
See the "Preparing for Introduction to All of Us Research Program" section of the supplement page for more guidance on what to prepare and review in advance. The full syllabus (including a day-by-day course outline) is also available to view.
IN-PERSON COURSES
Regression and Modeling in R
[dates and time TBA]
Instructor: Gustavo Amorim, PhD, research assistant professor of biostatistics
This course will cover advanced statistical topics frequently used in biological and medical research. Emphasis will be placed on practical applications of statistical methods and interpretation of the results. During this week, you will expand your understanding of the advantages and limitations of various methods, choose appropriate analytic approaches based on type of outcome variable and data structure, develop advanced statistical models in R, perform model diagnostic analyses, and interpret R output and analysis results.
Prerequisites: Biostatistics I or equivalent course(s). Students should be familiar with the basic notions and concepts of linear algebra and statistical modeling, types of variables (continuous, categorical, ordinal, etc.), common probability distributions (such as normal and binomial), and descriptive statistics, including summary statistics (mean, median, standard deviation, variance, etc.) and simple tests (t-test, Wilcoxon rank-sum test, chi-square test, etc.). See the "Preparing for Regression and Modeling in R" section of the supplement page for suggestions on what to prepare and review in advance.
Big Data in Biomedical Research
[dates and time TBA]
Instructors:
Qi Liu, PhD, associate professor of biostatistics and biomedical informatics
Yu Shyr, PhD, professor of biostatistics, biomedical informatics, and health policy
This course will explore statistical, bioinformatic, and computational methods and tools for analyzing big omics data in biomedical research, including experimental design for omics research, RNA-sequencing, single-cell RNA-sequencing, and statistical and bioinformatic methods in high-dimensional data. Students will gain practical experience with RNA-seq and single-cell RNA-seq analysis, including read mapping, quantification, differential expression, cell clustering, and marker gene identification, as well as performing functional interpretation of results.
Prerequisites: Students should have basic or entry-level knowledge of R programming, Linux/Unix commands, and biostatistics. See the "Preparing for Big Data in Biomedical Research" section of the supplement page for directions on what to prepare and review in advance, especially if you lack experience with R and Linux.
Introduction to Causal Inference
[dates and time TBA]
Instructor: Andrew Spieker, PhD, assistant professor of biostatistics
Many are familiar with the phrase “correlation does not imply causation,” but that then begs the question: what exactly is causation in the first place? In this five-day short course, we will introduce fundamentals of causal inference approaches. The first three days will provide an overview of commonly implemented causal inference methods, including standardization, matching, inverse-weighting, and instrumental variables. The fourth day will focus on methods for longitudinal data, and the fifth day will address miscellaneous topics, including sensitivity analyses and causal inference with survival outcomes. Throughout the course, emphasis will be placed on graphical representation of variables through “directed acyclic graphs” (i.e., DAGs) and software implementation.
Prerequisites: Some familiarity with basic statistics (including linear and logistic regression) and/or interest in designing and evaluating clinical trials. See the "Preparing for Introduction to Causal Inference" section of the supplement page for suggestions on what to prepare and review in advance.
Frequently Asked Questions
Where do your in-person courses take place?
The in-person courses will be held on the Vanderbilt University Medical Center campus, in the 2525 West End Avenue building. Live participation is expected, and some courses may feature small-group discussions. The sessions will not be recorded or streamed.
Meals and snacks are included with these intensive courses. We will provide a light continental breakfast before each morning class, and boxed lunches to all participants. Coffee, tea, and snacks will be available throughout each day.
I will be driving to campus to attend the Summer Institute. Where can I park my car?
When you register, please indicate that you will need parking. We will assist with making arrangements for a complimentary spot.
Will the instructors make reasonable accommodations for my disability?
Please contact us to discuss what is needed. All requests will be kept confidential. We are committed to maintaining an inclusive and accessible learning environment.
2525 West End is equipped with accessible parking, as well as ramps to the building from the parking garage, touch-open doorways, and an easy-to-access elevator bank.
Is there a lactation room?
Yes, in the Department of Biostatistics, on the tenth floor. Please contact the course administrator to arrange access.
Is vaccination and/or masking required?
At present, no. However, individuals may still choose to wear a mask in any area at Vanderbilt University Medical Center, and we ask all participants to respect this choice. We follow VUMC guidance on COVID-19 prevention, which may be updated if a new variant or other factors suggest an increased risk of spread.
How do I obtain a certificate or credit for this course?
A certificate of completion will be emailed to each participant after the end of the course. Academic course credit is offered only to Cancer Biologystudents for "Big Data in Biomedical Research." We do not grade or track the attendance of other participants.
I have a scheduling conflict. May I attend the in-person courses virtually, as a self-paced participant?
Recordings of the 2024 courses will not be available. We anticipate offering Coursera editions of some courses down the line, and hope you will take advantage of that option if your schedule does not allow for in-person participation.
Do you plan to offer these courses in the future?
After every Institute, we will review what worked and what needs to be adjusted, with timing and format among our considerations. We collect feedback from participants at the end of each course, including whether the instruction met their expectations and what they would like to see on offer. These help guide the planning and design of future Summer Institutes.
I have a question that hasn’t been answered yet. Whom do I contact?
Jena Altstatt, course administrator
Details subject to change without notice.