adv_singlecell_2022

Material for the "Advanced topics in single-cell analysis" course (2022 edition)

For more information and to apply, please visit: https://www.sib.swiss/training/course/20220426_ADVSC

Teachers:

• Emma Dann
• Pierre-Luc Germain
• Giovanni Palla
• Panagiotis Papasaikas
• Mark Robinson
• Sebastien Smallwood
• Charlotte Soneson
• Michael Stadler
• Kevin A Yamauchi

Program

Tuesday, April 26
9:00 - 9:30	Welcome and setup of working environment
9:30 - 10:00	Combining the best of two worlds: Python + R (M. Stadler, slides)
10:00 - 10:15	Break
10:15 - 11:15	Combining the best of two worlds: Python + R (M. Stadler)
11:15 - 12:00	Differential analysis (M. Robinson, P-L. Germain)
12:00 - 13:30	Lunch
13:30 - 15:00	Differential analysis (M. Robinson, P-L. Germain)
15:00 - 15:15	Break
15:15 - 16:30	RNA velocity (C. Soneson, slides)
16:30 - 16:45	Break
16:45 - 17:45	RNA velocity (C. Soneson)

Wednesday, April 27
9:00 - 10:00	Generating single-cell data (S. Smallwood, slides)
10:00 - 10:15	Break
10:15 - 11:15	Multi-omics (E. Dann, slides: google doc)
11:15 - 11:30	Break
11:30 - 12:30	Multi-omics (E. Dann)
12:30 - 14:00	Lunch
14:00 - 15:30	Multi-omics (E. Dann)
15:30 - 15:45	Break
15:45 - 17:30	Multi-omics (E. Dann)

Thursday, April 28
9:00 - 10:30	Spatial transcriptomics (G. Palla, K. Yamauchi, slides)
10:30 - 10:45	Break
10:45 - 12:00	Spatial transcriptomics (G. Palla, K. Yamauchi)
12:00 - 13:30	Lunch
13:30 - 15:30	Spatial transcriptomics (G. Palla, K. Yamauchi)
15:30 - 15:45	Break
15:45 - 17:30	Spatial transcriptomics (G. Palla, K. Yamauchi)

Friday, April 29
9:00 - 9:30	Interactive visualization with iSEE (C. Soneson, slides)
9:30 - 10:00	Deep generative networks (P. Papasaikas, slides)
10:00 - 10:15	Break
10:15 - 12:00	Deep generative networks (P. Papasaikas)
12:00 - 13:30	Lunch
13:30 - 15:30	Deep generative networks (P. Papasaikas)
15:30 - 15:45	Break
15:45 - 16:45	Deep generative networks (P. Papasaikas)
16:45 - 17:00	Wrap-up