Microbiome Data Analytics Boot Camp: Planning, generating, and analyzing 16S rRNA gene sequencing surveys

June 20-21, 2024 | Subscribe to hear about the next training

Registration is open! Join us for the next Microbiome Boot Camp on June 20-21, 2024.

The Microbiome Data Analytics Boot Camp is a two-day intensive training of seminars and hands-on analytical sessions to provide an overview of 16S rRNA gene sequencing surveys including planning, generating and analyzing sequencing datasets.

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Boot Camp Overview

Summer 2024 dates: Livestream, online training June 20-21, 2024; 12:00pm - ~8:00pm EDT

Amplicon sequencing of taxonomic marker genes such as the 16S rRNA gene in bacteria has been used over the last two decades to survey the microbiota of myriad environments. From soil to aquatic to human systems, 16S rRNA amplicon sequences are widely used to characterize the diversity and composition of the gut microbiome, discover novel microbes, and define how specific microbes link to environmental or host traits of interest. As a result, 16S rRNA amplicon surveys have proven invaluable in efforts designed to uncover the potential contribution of microbiomes to critical ecological and health processes.

This two-day intensive workshop will provide a rigorous introduction to the theory and methodology underlying the design, generation, and analysis of Amplicon Sequence Variant (ASV) based investigations of microbial communities. The workshop will introduce state-of-the-art techniques using the R language and environment. A team of leading experts in microbiome data analytics and statistics will offer a hands-on experience in learning how to implement these techniques by integrating publicly available data and R packages to explore and understand some of the pitfalls and information drawn from 16S rRNA data analysis. This workshop specifically trains participants in the use of the R programming environment for the analysis of microbiome sequence data, including the implementation of the DADA2 and phyloseq software packages. It will also introduce introductory concepts and methods in the generation and analysis of shotgun metagenomic data.

By the end of the workshop, participants will be familiar with the following topics:

The theoretical basis underpinning 16S rRNA investigations
Methodologies for generating 16S rRNA sequence data
16S sequence data quality control
Amplicon sequence variant inference
Taxonomic annotation
Biodiversity estimation
Principal Component Analysis and PERMANOVA
Taxon-covariate correlation and regression modeling
Introduction to machine learning in microbiome data
Phylogenetic analysis

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 workshop:

Each participant must have an introductory background in statistics.
Each participant must be familiar with R.
Each participant must have a computer with either Chrome or Firefox installed (latest update).

Instructors

Maude David, PhD, Assistant Professor, Department of Microbiology & Department of Pharmaceutical Sciences at Oregon State University. Dr. David’s laboratory studies gut-brain interactions to understand how the gut microbiota can impact our behavior. Her laboratory also works on identifying bottlenecks in microbiome data exploration and has been developing new biocomputing methods to improve sequencing data annotation and analysis. Her interest lies in using machine learning algorithms to extract meaningful information from massive datasets already publicly available such as the Human Microbiome Project.

Thomas Sharpton, PhD, Associate Professor, Department of Microbiology & Department of Statistics, Oregon State University. Dr. Sharpton applies systems biology tools to understand how nutritional and chemical exposure impacts the structure and function of the vertebrate gut microbiome, and how these impacts affect human health. He has published over 50 manuscripts pertaining to the bioinformatic analysis of microbial genomic and metagenomic data and directs the Oregon State University Microbiome Initiative. His current research includes defining how the microbiome modulates environmental exposure over lifespan, mining the gut microbiome for novel pharmaceuticals, and developing analytical resources to define how the microbiome links to health and disease.

Scholarships

Scholarships are available for the Microbiome Boot Camp.

Locations

Summer 2024: The Microbiome Data Analytics Boot Camp is a livestream, remote training. With instructors on the west coast, the Boot Camp will take place over live, online video on June 20-21, 2024 from 12pm EDT - ~8pm EDT (9am PDT - 5pm PDT). Please note this training is not a self-paced, pre-recorded online training.

Testimonials

"'Exceeded expectations' is definitely true. This training was extremely valuable. I feel I have the tools to do a complete start to finish analysis. The added benefit of talking to instructors about their views and experience on study design and other R/data analsyis questions was so appreciated. If the quality of workshops is this good for all SHARP programs, I want to sign up for them all! Thank you so much!" - Faculty member at University of Hawaii, 2023

"What a fantastic course, providing you with a foundational/fundamental framework to conduct microbiome analysis including: R-code scrips to plug and play with your own data and useful resource references. The team was amazing and very helpful." - Faculty member at Western University of Health Sciences, 2023

"As a microbiome newbie, the course was extremely comprehensive and provided me with the necessary tools to support my exploration and research in this area. The tools were excellent, and the instructors were very clear and supportive." - Faculty member at Rutgers School of Public Health, 2023

"This training was both insightful, challenging, and supportive! All of the instructors were great at explaining the complex topics related to 16S sequencing and analysis as well as machine learning." - Student at Oregon State University, 2023

Additional Testimonials

"It was the best workshop I have attended so far. Not only because of the topic, but also the instructors' expertise and their ability to explain complex issues simply and clearly." - Staff member at Institute of Nature Conservation of the Polish Academy of Sciences, 2022

"As a new student learning about the world of the microbiome, this course was a great tool. I got to learn the basics about 16S data generation and methods to help me analyze my own data in the future." - Student at University of Florida, 2022

"I came into this course with a very limited understanding of 16S data generation and analyses. I honestly wouldn't have known where to start! Now, I feel I have a great baseline understanding to be able to begin thinking of how to incorporate it into my own research." - Postdoc at Baylor College of Medicine, 2022

"This was a really fun training! I came into this program already having 16S amplicon sequencing data that was ready to be analyzed, so I enjoyed going through the lectures and then being able to edit the code for my own data right away." - Student at University of North Carolina at Chapel Hill, 2022

"Overall, I think this is an excellent overview of microbiome data analysis and common techniques/analyses used. This was a great "springboard" for beginners (like me!) to go on and play around in R on their own and increase their knowledge." - Postdoc at National University of Natural Medicine, 2022

"Great workshop -- provided excellent background knowledge and a lot of very useful code (while acknowledging the multitude of other tools/options out there in addition to the ones covered here). The learning environment was also good with options to ask questions in large group, small group, or on Slack to suit different preferences." - Faculty member at Brigham and Women's Hospital, 2021

"It's a great opportunity to learn the nuts and bolts of the analysis. I'm really glad I found the training and was able to sign up." - Government researcher, US Department of Agriculture, 2021

"Overall, this training was outstanding. The expertise of the instructors, the material provided and the general approachability of the group was wonderful. I highly recommend and wish I could take it again in 6-12 months to refresh." - Anonymous Oncology Fellow, 2021

"Very helpful and the best organized workshop I've ever attended. All instructors were not only knowledgeable, but helpful and approachable." - Abbi H., Postdoc at The University of Alabama at Birmingham

"Taking part in this workshop was an incredible opportunity! As an incoming graduate student, this course provided me with a variety of tools needed to become a more proficient R programmer and effectively explore microbiome research!" - Caroline H., Student at Oregon State University, 2021

"The microbiome course material was presented in a very organized fashion that clarified concepts and methods for microbiome analysis while at the same time providing the latest and most current (timely) information on these topics as well as future directions." - Anonymous Faculty member, 2021

"I've attended other microbiome programs, and this one is probably the best. The R coding tools that we were given are exceptional. I'd highly recommend this course to other colleagues." - Faculty member at Vanderbilt University Medical Center, 2020 virtual training

"This was an excellent training for what I needed. The background information really built into microbiome analysis in a tangible way, and I look forward to having the materials from this course as a resource in the future." - Postdoc at North Carolina State University, 2020 virtual training

"Most well organized and comprehensive workshop I've ever taken. Coming from a different field, I am inspired to incorporate these ideas into my future endeavors." - Student at the University of Chicago, 2020 virtual training

"The instructors were very knowledgeable and thorough with the concepts and ready to answer the questions." - Corporate Staff Member at AbbVie, 2020 virtual training

"Great introduction to learning 16S microbiome analysis in R." Faculty member at Wake Forest University, 2020 virtual training

"All the instructors were great and the hands on practicals were valuable to learning the concepts presented in lectures. I highly recommend this for people who want to learn how to handle and analyze microbiome data." - Student at Emory University, 2020 virtual training

"This was so useful and has made me feel competent to take on my own analyses." - Postdoc at University of California, San Francisco, 2020 virtual training

"This course provided an extensive amount of knowledge of analyzing microbiome data in a friendly and productive manner. Even though I had little experience of microbiome analyses going in, this course provided me with a wealth of information that I will use throughout my future career." - Student at the University of Iowa, 2020 virtual training

"I prefer trainings that plunge you immediately into how to practically implement what you're learning--this was that type of training. The instructors were very knowledgable and friendly, the R exercises were well thought out, and the online format worked surprisingly well. Overall an excellent course." Faculty member at Georgetown University, 2020 virtual training

Registration Fees

	Early-Bird Rate (through 4/10/24)	Regular Rate (4/11/24 - 6/13/24)	Columbia/OSU Discount*
Student/Postdoc/Trainee	$995	$1,195	10%
Faculty/Academic Staff/Non-Profit Organizations/Government Agencies	$1,195	$1,395	10%
Corporate/For-Profit Organizations	$1,395	$1,595	NA

*Columbia/OSU 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. To access OSU discount, please email ColumbiaSHARP.Microbiome@gmail.com.

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.Microbiome@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.Microbiome@gmail.com. In the event Columbia must cancel the event, your registration fee will be fully refunded.