happy to know people have found this helpful! here is a link to the course materials drive.google.com/drive/u/1/folders/1kuGHpbJFs2qy-Q2YzHXpsuqk7Wfe6hAT
Flow cytometry's result (protein expression level) is not directly linked to single cell sequencing result, and that's where cite-seq or related technique come into play.
Thank you soooo much my UCLA sister. Im your neighbor from UCSD :D This content is awesome, very comprehensive and clearly-explained. Would it be possible for you to share the slides? I totally understand if there's copyright issue. These are such great learning materials
1:10 learning objectives
4:10 workshop overview
5:55 intro/motivation for scRNAseq
1:18:40 scRNAseq analysis workflow
2:26:20 scanpy
Amazing content. In-depth breakdown. Really interesting with my favorite subject area.
Thanks for the workshop, it is really good introductory workshop for scRNA-Seq Analysis.
Wonderful video! Thank you so much for sharing!
happy to know people have found this helpful! here is a link to the course materials drive.google.com/drive/u/1/folders/1kuGHpbJFs2qy-Q2YzHXpsuqk7Wfe6hAT
Thank you
Thank you ;)
Thank you
Amazing content! Where could I download that dataset?
Really amazing video. Like others even I am interested in downloading the data , scripts etc . Could you please share the link
Flow cytometry's result (protein expression level) is not directly linked to single cell sequencing result, and that's where cite-seq or related technique come into play.
Thank you soooo much my UCLA sister. Im your neighbor from UCSD :D This content is awesome, very comprehensive and clearly-explained. Would it be possible for you to share the slides? I totally understand if there's copyright issue. These are such great learning materials
Can you please share the material
Amazing content! Can you please share the slide?
please share data ...
Share the repository please.
Thanks. could you please share the python scripts?
Can you share the codes?
Thanks for this amazing classes.