Multi-omics Boot Camp: Analysis of Omics Data for Research Studies
June 12-14, 2024 | Livestream, virtual
The course has reached capacity! Sign up below to join the waitlist for the Multi-omics Boot Camp on June 12-14, 2024.
The Multi-omics Boot Camp is a three-day intensive boot camp of seminars and hands-on sessions to provide an overview of concepts and methods used to analyze multiple omics data in observational studies. Specific topics will include integrating germline genetic, gene expression, and exposomic data, gene-environment interaction, mediation, and polygenetic risk scores for assessing risk, estimating subgroups, and selecting relevant features.
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Jump to: Overview | Audience & Requirements | R Tutorials | Instructors | Scholarships | Locations | Testimonials | Registration Fees | Additional Information
Boot Camp Overview
Summer 2024 dates: Livestream, online training June 12-14, 2024; 12pm - ~6:15pm EDT
Many observational studies are now leveraging modern technologies to measure multiple types of omic data. Omic tools can assist in better characterizing risk factors (e.g. germline genetics, exposomics), providing measurements for intermediate variables that may capture the underlying mechanism (e.g. transcriptomics, proteomics, metabolomics, and the microbiome), or defining an outcome of interest. In this context, the investigator is often confronted with an analytic decision on a continuum between simplicity and complexity. Simple approaches often treat sets of variables in a pairwise independent manner, sacrificing joint evaluation for benefits in interpretability. At the other extreme, complex methods may more-completely model the joint omics structure, but can sacrifice interpretability. This workshop will cover several different approaches to the analysis of multiple omic data, with a focus on the tradeoffs between simple and complex approaches.
This three-day intensive workshop will provide an overview of multiple approaches to analyze multiple omic data types measured on the same individuals or via the use of summary statistic data. Instructors have experience in developing and applying methods for omic analysis in genetic and environmental epidemiology and are members of an active program project focused on developing statistical methods for integrated analysis. The workshop will include seminar lectures with hands-on computer lab sessions to put concepts into practice. Since the analysis of multi-omic data is broad in scope, the workshop will survey a range of approaches and highlight the appropriate application and interpretation of each approach for specific research questions. The lab sessions will provide an opportunity to work hands-on with different types of omic data.
By the end of the workshop, participants will be familiar with the following topics:
- Data reduction, including clustering.
- Regression analysis, including regularized regression, hierarchical models, and partial least squares.
- Interaction analysis and Genome-wide interaction scans (GWIS).
- Mediation analysis.
- Polygenic/polyexposure analysis.
- Integrative analysis using genome-wide association study (GWAS) summary statistics.
Audience and Requirements
Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this training:
- Each participant must have an introductory background in statistics and epidemiology.
- Each participant must be familiar with R.
- Each participant is required to have a personal laptop/computer and a free, basic RStudio Cloud account. All lab sessions will be done using RStudio Cloud.
R Tutorials
Knowing basic R platform and commands is required for the Boot Camp as noted in the requirements above. If you are new to R or need a refresher, you can review the below tutorials to be well prepared:
- R Programming Tutorial - Learn the Basics: A free datalab.cc class on R fundamentals
- Once you create your free, basic RStudio Cloud account for the training: Primers on Programming Basics and Visualization Basics.
- SHARP Program RStudio Cloud Tutorial: This self-paced tutorial from the Columbia SHARP Program walks through the Cloud Platform you will use at the training, as well as some basic exercises. We recommend this tutorial if you have not used the Cloud version of RStudio before, or if you are a beginner user of R.
If you have any specific questions about R and R studio in the context of the Multi-omics Boot Camp, please email the Multi-omics Team.
Instructors
Training Director: David Conti, PhD, Professor of Preventive Medicine, Center for Genetic Epidemiology, Keck School of Medicine of USC.
William Gauderman, PhD, Professor of Preventive Medicine, Preventive Medicine, Keck School of Medicine of USC.
Jesse Goodrich, PhD, Assistant Professor of Population and Public Health Sciences, Keck School of Medicine of USC.
Juan Pablo Lewinger, PhD, Assistant Professor of Clinical Population and Public Health Sciences, Keck School of Medicine of USC.
Nicholas Mancuso, PhD, Assistant Professor of Preventive Medicine, Center for Genetic Epidemiology, Keck School of Medicine of USC.
Kimberly Siegmund, PhD, Professor of Preventive Medicine, Keck School of Medicine of USC.
Scholarships
Training scholarships are available for the Multi-omics Boot Camp.
Locations
Summer 2024: The Multi-omics Boot Camp is a livestream, remote training that takes place over live, online video. With the instructors on the west coast, the Boot Camp will take place on June 12-14, 2024 from 12pm - ~6:15pm EDT (9am - ~3:15pm PDT). Please note this training is not a self-paced, pre-recorded online training.
Testimonials
"It was a fantastic, very well organized and comprehensive bootcamp! The instructors were highly knowledgeable and very responsive to answering all questions. The information and methods covered were state-of-the-art in the field. I would highly recommend it to anyone working with high-dimensional data." - Faculty member at Harvard, 2023
"Multi-omics Boot Camp helps me to understand the integration of omics data in a comprehensive manner. Overall course was neatly organised and very recommended for those that interested/working with multi-omics data." - Postdoc at RadBoud University, 2023
"Excellent workshop that provided a fantastic introduction to multi-omic methods. This helped me better understand foundational concepts in multi-omics analyses that I will definitely use in my own future research."-Faculty member at University of Southern California, 2023
Additional Testimonials
"The information provided was on point and I will definitely be using the concepts in my own research! The instructors and TAs were great and everyone was willing to answer questions and provide more detail." - Staff member at Medical College of Wisconsin, 2022
"The information was organized logically and presented in a clear and concise way. I appreciated the hands-on opportunity with the lab. The faculty were engaging and knowledgeable." - Faculty member at Washington University in Saint Louis, 2022
"Great overview on current literature for multi-omics analyses with amazing instructors and experts in the field." - Postdoc at Brigham and Women's Hospital and Harvard Medical School, 2022
"The boot camp provided a succinct, yet comprehensive, overview of the methods/approaches used in multi-omics research and how to apply them. The instructors were excellent; they taught the information clearly, provided great lecture notes, and efficiently demonstrated how to apply the various R code used in multi-omics research during the lab sessions." - Student at Columbia University, 2022
"It was just the right balance of lecture and labs. Overall very helpful!" - Staff member at Duke University Health System, 2022
"This camp improved my knowledge and abilities to employ cutting-edge statistical principles and modelings to explore the high dimensional omics data and address the scientific hypothesis." - Faculty member at Eastern Virginia Medical School, 2021
"Extremely useful course with a great balance of theoretical concepts and hands-on application using R code. Covered state-of-the-art techniques with experienced and knowledgeable instructors." - Faculty member at Brigham and Women's Hospital, 2021
"This bootcamp was fantastic! The instructors did a great job of clearly explaining complex topics and I feel like I left with the practical skills to be able to apply them to my own research." - Postdoc at Columbia University Mailman School of Public Health
"Well prepared and organized. All teachers very helpful and patient." - Beata M., Postdoc at Albert Einstein College of Medicine, 2021
"A great methods-driven overview of multi-omics, with applications to multiple research areas in observational research. I found the examples and overview of programming to be a great pairing, as it makes the tools learned immediately applicable."- Student at University of Texas Health Science Center at Houston, 2021
Registration Fees
| Early-Bird Rate (through 4/10/24) | Regular Rate (4/11/24 - 6/5/24) | Columbia Discount* | |
|---|---|---|---|
| Student/Postdoc/Trainee | $1,195 | $1,395 | 10% |
| Faculty/Academic Staff/Non-Profit Organizations/Government Agencies | $1,395 | $1,595 | 10% |
| Corporate/For-Profit Organizations | $1,595 | $1,795 | NA |
*Columbia Discount: This discount is valid for any active student, postdoc, staff, or faculty at Columbia University. If paying by credit card, use your Columbia email address during the registration process to automatically have the discount applied. If paying by internal transfer within Columbia, submit this Columbia Internal Transfer Request form to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.
Invoice Payment: If you would prefer to pay by invoice/check, please submit this Invoice Request form to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.
Registration Fee: This fee includes course material, which will be made available to all participants both during and after the conclusion of the training.
Cancellations: Cancellation notices must be received via email at least 30 days prior to the training start date in order to receive a full refund, minus a $75 administrative fee. Cancellation notices received via email 14-29 days prior to the training will receive a 75% refund, minus a $75 administrative fee. Please email your cancellation notice to ColumbiaSHARP.Multiomics@gmail.com. Due to workshop capacity and preparation, we regret that we are unable to refund registration fees for cancellations <14days prior to the training.
If you are unable to attend the training, we encourage you to send a substitute within the same registration category. Please inform us of the substitute via email at least one week prior to the training to include them on attendee communications, updated registration forms, and materials. Should the substitute fall within a different registration category your credit card will be credited/charged respectively. Please email substitute inquiries to ColumbiaSHARP.Multiomics@gmail.com. In the event Columbia must cancel the event, your registration fee will be fully refunded.
Additional Information
- Join Waitlist
- Subscribe for updates on new Boot Camp details and registration deadlines.
- Contact the Multi-omics Boot Camp team.
The Multi-omics Boot Camp is hosted by the Columbia Mailman School of Public Health's SHARP Program.
Jump to: Overview | Audience & Requirements | R Tutorials | Instructors | Scholarships | Locations | Testimonials | Registration Fees | Additional Information