During this one-day hands-on workshop, we will cover techniques, platforms and methods that are used in analyzing single cell data. The workshop has two hands-on sessions: an introductory session in the morning and a more advanced session in the afternoon. The morning session will focus on analysis using Seurat and Monocle. In the afternoon, we will have three advanced hands-on sessions ranging from network analysis of single cell datasets in Cytoscape, normalization and differential analysis outside of Seurat and querying a Single Cell Atlas for cell types. Laptop required.

Instructor’s note: Please sign up only for the session that matches your experience level and learning goals. Review the requirements and details below before registering for a session.

Basic Session (9am-12pm):

Required experience

• Familiarity with R and RStudio (e.g., reading in files, working with lists and dataframes)
• Some exposure to RNA-seq datasets

Part 1: Set-up with breakfast (9-10am)

Part 2: Single Cell RNA-seq Analysis with Seurat - David Joy (10am-12pm)

A Brief Introduction to Single Cell Data in R (10:00-10:30)

• Intro to R-markdown notebooks
• Understanding single cell counts data
• Loading counts data into Seurat

Single Cell Analysis using Seurat (10:30-11:30)

• The Seurat normalization and clustering pipeline
• Unbiased cluster analysis
• Assigning cell type identities
• Subsetting and subpopulation analysis

Pseudo Time Analysis using Monocle (11:30-12:00)

• The Monocle normalization and clustering pipeline
• Unbiased trajectory analysis
• Trajectory analysis using experimental annotations

Advanced Session (12pm-5pm):

Required experience

• Comfortable with R, RStudio and analytical software
• Prior experience running Seurat and working with single cell data
• Ready for more advanced topics and methods

Part 3: Set-up and Q&A with lunch (12 - 2pm)

Part 4: Analysis Beyond Seurat (2-5pm)

Network analysis of single cell datasets in Cytoscape (2:00-2:45)

• Introduction to Cytoscape for network visualization
• Introduction to network interaction databases and enrichment analysis
• End-to-end functional characterization of clusters resulting from single cell analysis

Normalization and differential expression (2:45-3:45)

• Short Introduction to Experimental Design, Batch Effects, P-values and Multiple testing
• Normalization of reads for potential batch effects
• Statistically rigorous association of gene expression with variable of interest

Querying a Single Cell Atlas for Cell Type (3:45-4:15)

• Load single cell atlas and counts for the cells to query
• Reformat data to the SingleCellExperiment class
• Create an index for the atlas
• Query the atlas
• Visualize the results

Q&A with Instructors (4:15-5:00)