Single Cell Analysis Boot Camp: Systems Biology Methods for Analysis of Single Cell RNA-Seq

May 20-21, 2024 | Livestream, virtual

This course has reached capacity! Join the waitlist for the next livestream Single Cell Analysis Boot Camp on May 20-21, 2024.

The Single Cell Analysis Boot Camp is a two-day intensive training of seminars and hands-on analytical sessions to launch students on a path towards mastery of scRNASeq data analysis methods used in health studies.

Join Waitlist

Subscribe for updates on scholarship dates, deadlines, and announcements.

Single Cell Analysis Overview

Summer 2024 dates: Livestream, online training May 20-21, 2024; 10am EST - ~5:15pm EST.

Recently developed methods for scRNASeq analysis focus on the comparison of whole transcriptional profiles to separate hundreds or thousands of single cells into several distinct populations. These methods are largely unsupervised, allowing researchers to explore new and novel populations. Interpreting the biology of these novel populations is challenging and is a major focus of cutting-edge systems biology methodology that can deconvolve the high dimensional data into meaningful components.

This two-day intensive boot camp starts with a fast-paced training session on single cell data collection and basic analysis in the first half-day, then continues with in-depth sessions on advanced methods for phenotyping single cell populations using systems-biology approaches. Led by a team who have invented several of the methods used in network biology and single-cell transcriptome analysis, we demonstrate how to use network models to convert gene expression profiles into protein activity profiles, and how to transfer knowledge between established bulk datasets and novel single-cell data. We expect that, during this hands-on workshop, participants will acquire enough knowledge to plan and perform scRNAseq analyses.

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

Gene Expression Analysis of scRNA data (pre-processing, quality control, filtering, normalization)
Cluster Analysis
Cell Type Identification
Regulatory Network Analysis
Master Regulator 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 a few requirements to attend this training:

Each participant must have an introductory background in statistics.
Each participant must be familiar with R & Python.
Each participant must have a free, basic RStudio Cloud account prior to the first day of the workshop.
Each participant must have a free basic Google/Gmail account to access Google Colab for the lab sessions.

R Tutorials

Knowing basic R platform and commands is required for the Boot Camp as noted in prerequisites above. This training will use RStudio Cloud (now called Posit). 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 Boot Camp, please email the Single Cell Team.

Instructors

Boot Camp Director: Lorenzo Tomassoni, PhD, Postdoctoral Research Scientist, Department of Systems Biology, Columbia University. Dr. Tomassoni holds a master’s degree in computer science and a PhD in Computational Systems Biology both from the University of Perugia, Italy. During the last year of his PhD he joined the Laboratory of Dr. Andrea Califano, at Columbia University in New York City, where he studied regulatory-network-based methodologies for the systematic analysis and integration of multi-omics data with specific focus on single-cell data. Then, as a Postdoctoral Research Scientist, he developed novel algorithms and approaches for the analysis of Single-Cell RNA Seq data and he is leading several projects in the field of drug discovery using human-related single-cell data with particular interest in brain and pancreatic tumors.

Ester Calvo Fernández, PhD Candidate, Departments of Pathology and Cell Biology and Systems Biology, Columbia University. Ester earned her PharmD from the University of Barcelona, in Barcelona, Spain. After that, she was a St. Baldrick's fellow at the University of Michigan for two years, where she studied in vivo characterization of modulators of Notch signaling in mouse models of Sonic Hedgehog medulloblastoma tumorigenesis. She is now a PhD candidate in Dr. Andrea Califano's lab with a strong background in pharmacology and molecular biology. Her current research focuses broadly on applying novel systems biology approaches to defining and targeting master regulator dependencies from single-cell RNA-seq in diffuse midline gliomas (DMG). Her research focuses on dissecting the heterogeneity of these tumors at the single cell level, defining tumor checkpoint modules representing pharmacologically accessible, mechanistic determinants of molecularly-distinct DMG cell states, and predicting and validating novel therapeutic strategies for preclinical and clinical testing to improve outcomes in this fatal disease. She is also involved in the interrogation of genome-wide, experimentally dissected druggable gene regulatory networks to elucidate several mechanisms of actions of these compounds at the single cell level, as well as in other Pancreatic Ductal Adenocarcinoma (PDA) and Non-Small Cell Lung Cancer single-cell studies.

Aleksandar Obradovic, MD/PhD Candidate, Columbia University.

Alessandro Vasciaveo, PhD, Associate Research Scientist, Columbia University.

Luca Zanella, PhD Candidate, University of Padova; Staff Associate, Columbia University.

Keynote Speaker: Peter Sims, PhD, Systems Biology, Columbia University

Former Instructors and Keynote Speakers

Aaron Griffin, Medical Scientist Training Program and Department of Systems Biology, Columbia University Irving Medical Campus; Single Cell Analysis Boot Camp Instructor, 2022.

Benjamin Izar, MD, PhD, Assistant Professor of Medicine at CUIMC; Keynote Speaker, 2021.

Pasquale Laise, PhD, Director of Single Cell Systems Biology, DarwinHealth Inc. and Adjunct Associate Research Scientist, Systems Biology, Columbia University; Single Cell Analysis Boot Camp Instructor, 2019 and 2021.

Heeju Noh, PhD, Systems Biology, Columbia University; Single Cell Analysis Boot Camp Instructor, 2021 and 2022.

Evan Paull, PhD, Systems Biology, Columbia University; Single Cell Analysis Boot Camp Instructor, 2019.

Peter Sims, PhD, Systems Biology, Columbia University; Keynote Speaker, 2019 and 2022.

Lukas Vlahos, PhD Candidate, Department of Systems Biology, Columbia University; Single Cell Analysis Boot Camp Instructor, 2021 and 2022.

Scholarships

Training scholarships are available for the Single Cell Analysis Boot Camp.

Locations

Summer 2024: Livestream, remote training that takes place over live, online video on May 20-21, 2024 from 10am EST - ~5:15pm EST.

Please note this training is not a self-paced, pre-recorded online training.

Testimonials

"The Single Cell Analysis Boot Camp was incredibly helpful for understanding not only the basics of what single cell sequencing is and how it works, but the different information that can be gained and how to analyze the data to obtain this information. Very well worth the cost." - Student at University of Pittsburgh, 2023

"The Single Cell Analysis Boot Camp did an excellent job at providing a basic introduction to using scRNA-seq technologies and how this can be applied to our research. Instructors made difficult topics easy to understand." - Student at Albany Medical College, 2023

"This gives a great basis for understanding single-cell RNA-seq analysis. It's definitely not just another Seurat walkthrough." - Postdoc at Oregon Health & Science University, 2023

Additional Testimonials

"The Single Cell Analysis Boot Camp was a great introduction to the many exciting approaches and technologies used in the single cell field. I'm very excited to see what these techniques will reveal about my own data and the biological questions they'll spark!" - Student at University of California - Santa Cruz, 2022

"This was a very organized and expertly conducted workshop that provided an excellent foundation for my planned scRNA-Seq research studies. After completing the pre-course assignments, I felt well prepared for the course despite having little practical experience with the topics." - Faculty member at University of Michigan, 2022

"An excellent introduction to scRNAseq, with focus on computational tools. Super friendly and approachable instructors." - Postdoc at Columbia University, 2022

"This was a well-organized workshop taught by people who really know their stuff. It is appropriate for a range of investigators who want to learn more about the basics of scRNA-Seq analysis." - Faculty member at Penn State College of Medicine, 2022

"This boot camp was very well structured for someone with limited background and experience with single cell techniques and analysis. I appreciated the introductory material to experimental design and equipment/procedure before delving into more advanced methods and analysis. It was very well done, thorough in the fundamentals while showing the new exciting, more exploratory, applications. I would 100% recommend to anyone interested in learning about single cell analysis." - Faculty member at Washington University in St. Louis, 2022

"The Boot camp included a mix of pragmatic instruction regarding sample preparation, initial analyses for data quality, basic clustering and cell type assignments, and more advanced analyses to identify regulatory networks in single cell RNA Seq data. My lab is new to single cell RNA Seq, and the Boot camp was on target for my needs." - Faculty member at University of Texas Health Science Center Houston, 2021

"Useful program that offered lots of tools, whether you're just starting scSeq analysis or have experience." - Postdoc at Emory University, 2021

"I learned so much! I came in with no experience, and now feel I have the tools to start working with some real data sets and am better equipped to understand publications that use this technology." - Postdoc at University of Colorado Boulder, 2021

"Well planned and wasn't overwhelming. The lectures before coding helped make sense of what we were doing." - Postdoc at Columbia University, 2021

"Thanks to this workshop, I now have the tools I need to better explore single cell analysis on my own moving forward. I feel more confident in taking ownership over my future single cell studies, from experimental design to quality control and further downstream analyses." - Student at Boston University School of Medicine, 2021

"Great balance of lecture and hands on material to get a basic understanding of scRNA-Seq analysis that can be applied to my own data." - Gabriel G., Data Analyst, 2019

"All of the teachers/speakers were highly knowledgeable and great communicators, their clear expertise was appreciated." - Anonymous Faculty member, 2019

"This was a well-constructed workshop to provide attendees the basic tools to run a bioinformatic workflow for a scRNA analysis on their own. The instructors were experts in the field, presented material that was well-balanced between lectures and hands-on labs, were attentive to address questions and ensured that all participants were able to run through the labs." - Maya D., Icahn School of Medicine at Mount Sinai, Postdoc, 2019

"Great analysis camp- gives code for all tools needed for basic and more advanced scRNAseq analysis. Great jumping off point for researchers experienced with bulk analysis to start with single cell analysis." - Anonymous Student, 2019

"I would highly recommend the Single Cell Analysis Boot Camp to anyone looking to learn more about analyzing single cell transcriptomic data. The course offers a good balance between improving conceptual understanding as well as learning how to apply specific analysis tools." - Maria S., Memorial Sloan Kettering Cancer Center, Graduate Student, 2019

"Great for those who are just entering to scRNA-seq field and want to understand the basics. Also good if you have background but feel less confident whether you analyze your data according to the standards on the field." - Anonymous Postdoc, 2019

Registration Fees

	Early-Bird Rate (through 4/10/24)	Regular Rate (4/11/24 - 5/13/24)	Columbia 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 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 Columbia.scRNASeq@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 Columbia.scRNASeq@gmail.com. In the event Columbia must cancel the event, your registration fee will be fully refunded.