W20: Single-Cell RNA-Seq Analysis with Python - Day 1

UCLA QCBio Collaboratory

UCLA QCBio Collaboratory

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Published 2021-05-18

All Comments (17)

@sfmambero 2 years ago

1:10 learning objectives 4:10 workshop overview 5:55 intro/motivation for scRNAseq 1:18:40 scRNAseq analysis workflow 2:26:20 scanpy
@esa3296 2 years ago

Thanks for the workshop, it is really good introductory workshop for scRNA-Seq Analysis.
@chrisjmolina 1 year ago

Wonderful video! Thank you so much for sharing!
@hasithasampath1191 1 year ago

Amazing content. In-depth breakdown. Really interesting with my favorite subject area.
@MegaGmail007 1 year ago

Thanks for this amazing classes.
@abraaoandrade141 2 years ago

Amazing content! Where could I download that dataset?
@megaland4542 2 years ago

Can you please share the material
@mihirswimmer 2 years ago

Really amazing video. Like others even I am interested in downloading the data , scripts etc . Could you please share the link
@BreanneSparta 1 year ago

happy to know people have found this helpful! here is a link to the course materials https://drive.google.com/drive/u/1/folders/1kuGHpbJFs2qy-Q2YzHXpsuqk7Wfe6hAT
@yfg7691 2 years ago

Amazing content! Can you please share the slide?
@ariannali7888 11 months ago

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
@jiangxu3895 2 years ago

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.
@otaviocoutinho2855 2 years ago

Share the repository please.
@conlosjuguetesdemihijo6310 2 years ago

please share data ...
@fateme7799 1 year ago

Thanks. could you please share the python scripts?
@utkukaba 2 years ago

Can you share the codes?