Single Cell Genomics Day: A Practical Workshop


Where:NYU Center for Genomics and Systems Biology
When:Friday March 22, 2019 8:30 AM to 3:00 PM EST
Registration:You can register to attend here


Recent developments in molecular biology, microfluidics, and computational biology have transformed the field of single cell genomics. However, the breathtaking pace of technology development has given rise to a multitude of molecular protocols, commercial systems, and computational challenges.

The Satija Lab is excited to host the Third Annual Single Cell Genomics Day on Friday, March 22, 2019. This workshop will begin with an overview of exciting developments in the field over the past year, followed by in-depth presentations with an emphasis on practical details and considerations. Our goal is not to fully describe the details of each method, but instead to highlight the intuition and key use cases that can help motivate new users to get started.

Come to:

  • Learn about cutting-edge molecular technologies including: single nucleus ATAC-seq, spatial measurements of single cell expression, and multi-modal profiling approaches.
  • Hear about recent updates to widely used commerical systems, and contrasting home-brew workflows.
  • Get a practical introduction to recently developed computational techniques, including methods for data integration, organism-scale developmental reconstruction, and deep learning applications for single cell data.
  • Share ideas, troubleshoot experiments, and ask questions
  • Hear keynote presentations from:
    • Jeff Moffitt Harvard Medical School
    • Darren Cusanovich University of Arizona
    • Jeff Farrell Harvard Unviersity

Single Cell Genomics Day will be held at NYU Center for Genomics and Systems Biology, with check in beginning at 8:30 AM. Please register in advance to attend in person. The workshop is free for all participants, thanks to generous support from the NYU Biology department and Center for Genomics and Systems Biology.

Video livestream

We would like to acknowledge the generous support of the Chan Zuckerberg Initiative, which allowed us to provide a video livestream of all presentations. We will be posting slides, references, and selected videos from the workshop in the near future.


9:00 — 9:45Rahul Satija NYGC/NYU
Download Slides, Summary and References
Single-cell genomics: Recent advances and future directions
View the talk here
9:45 — 10:15Peter Smibert NYGC Technology Innovation Lab
Download Slides
Multi-modal single-cell analysis
Topics: ECCITE-Seq, single cell chromatin+RNA, single cell calling cards
10:15 — 11:00Jeff Moffitt Harvard Medical School
Imaging the transcriptome: Mapping the brain with MERFISH
11:00 — 11:15Coffee Break
11:15 — 11:45Grace Zheng 10X Genomics
Dissecting complex systems with multidimensional data
Topics: scATAC-seq, spatial gene expression, surface protein + antigen receptors
11:45 — 12:30Darren Cusanovich University of Arizona
Single-cell genomics via Combinatorial Indexing: A scalable and adaptable framework
12:30 — 13:15Lunch
13:15 — 13:45Andrew Butler, Shiwei Zheng NYGC/NYU
Download Slides
Introduction to Deep Learning methods for single-cell analysis
Topics: Neural networks, autoencoders, VAE, GAN
13:45 — 14:30Jeff Farrell Harvard University
Reconstruction of developmental trajectories during zebrafish embryogenesis
14:30 — 15:00Tim Stuart NYGC/NYU
Download Slides
Integration and harmonization of single-cell data
Topics: Batch correction, cross-modal integration, transfer learning


Additional resources

Below, we list a few useful resources for those who would like to a brief introduction to the field prior to the workshop.

Integrative single-cell analysis. (Stuart and Satija., 2019) [PubMed]
Our recent overview of multi-modal technologies and computational integration methods for single-cell data.

A practical guide to single cell RNA-seq for biomedical research and clinical applications. (Haque et al., 2017) [PubMed]
An excellent overview of single cell genomics, for those new to the field.

Choosing a single cell technology. (Satija Lab) [PDF Slides]
From our first single cell genomics day. Covers the strengths, weaknesses, and ideal uses cases for common technology platforms.

Computational and analytical challenges in single-cell transcriptomics. (Stegle, Teichmann, and Marioni, 2015) [PubMed]
A broad and comprehensive discussion of analytical challenges for single cell analysis.

Power analysis of single-cell RNA-sequencing experiments. (Svensson et al., 2017) [PubMed]
A comprehensive technical benchmarking of single cell technologies.

Methods and challenges in the analysis of single-cell RNA-sequencing data. (Camara, 2017) [Link]
A concise overview, focusing on recent analytical developments in the field.