Course material
Section outline
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Wednesday, May 27
9:00 - 10:30
Welcome and Introduction (all)
Course overview, expected background
(R/python, single cell analysis workflow links, M. Stadler)Introducing participants (“ice breaker”, polls, …, C. Soneson)
Setup of working environment
Slack workspace
Zoom (M. Stadler, C. Soneson, P. Papasaikas)
Renkulab (TBD)
10:30 - 10:45
Break
10:45 - 11:30
Combining the best of two worlds: Python + R
(interactive exercise, M. Stadler)11:30 - 11:45
Break
11:45 - 12:30
Combining the best of two worlds: Python + R (continued)
12:30 - 13:30
Lunch
13:30 - 14:30
Python + R (continued)
14:30 - 14:45
Break
14:45 - 15:30
Beyond cellranger: Quantification of gene expression
(presentation, A. Srivastava)15:30 - 15:45
Break
15:45 - 16:45
Quantification of gene expression (exercises, A. Srivastava)
16:45 - 17:00
Break
17:00 - 18:00
Quantification of gene expression (continued)
Thursday, May 28
9:00 - 10:00
RNA velocity (presentation, C. Soneson)
10:00 - 10:15
Break
10:15 - 11:15
RNA velocity (exercises, C. Soneson)
11:15 - 11:30
Break
11:30 - 12:30
RNA velocity (continued)
12:30 - 14:00
Lunch
14:00 - 15:00
Spatial transcriptomics (presentation, A. Andersson)
15:00 - 15:15
Break
15:15 - 16:15
Spatial transcriptomics (exercises, A. Andersson)
16:15 - 16:30
Break
16:30 - 17:30
Spatial transcriptomics (continued)
Friday, May 29
9:00 - 10:00
Working with on-disk data formats (presentation, M. Smith)
10:00 - 10:15
Break
10:15 - 11:15
Working with on-disk data formats (exercises, M. Smith)
11:15 - 11:30
Break
11:30 - 12:30
Working with on-disk data formats (continued)
12:30 - 13:30
Lunch
13:30 - 14:30
Deep Generative Networks (presentation and exercises, P. Papasaikas)
14:30 - 14:45
Break
14:45 - 15:45
Deep Generative Networks (continued)
15:45 - 16:00
Break
16:00 - 17:00
Deep Generative Networks (continued)
17:00 - 17:30
Wrap-up (feedback form, slack workspace, all)