Automatic cell-annotation for single-cell RNA-Seq data: A detailed SingleR tutorial (PART 2)
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- čas přidán 29. 06. 2024
- Continuing the discussion from previous video about cell type annotation, in this video I walk through various strategies to perform cell type annotation using multiple reference datasets. Furthermore, I talk about strengths and pitfalls of each strategy and demonstrate how to annotate cell types in #SingleR using multiple reference datasets from celldex package.
I hope you find this video helpful! Leave your thoughts in the comment section below!
▸ Part 1 of this video:
• Automatic cell-annotat...
▸ Link to Data:
www.10xgenomics.com/resources...
▸ Link to Code:
github.com/kpatel427/CZcamsT...
▸ Resources/Vignettes:
1. www.nature.com/articles/s4159...
2. bioconductor.org/books/release...
3. bioconductor.org/books/3.14/OS...
Chapters:
0:00 Intro
1:03 Strategies for using multiple reference datasets for annotation
5:38 Study design and goal of the analysis
7:27 Fetching 2 reference datasets from celldex package
8:30 Annotation strategy 1: Using a combined reference
13:42 Visualize results of strategy 1 in a UMAP
17:21 Annotation strategy 2: Comparing scores across references
19:56 Which reference scored the best for which label?
21:33 How to get the markers for each label from individual references?
22:24 Combined diagnostic heatmap
24:47 Lack of consistency in labels across references
26:05 Annotation strategy 3: Using harmonized labels
29:46 How to map cell ontology terms to labels?
You can show your support and encouragement by buying me a coffee:
www.buymeacoffee.com/bioinfor...
To get in touch:
Website: bioinformagician.org/
Github: github.com/kpatel427
Email: khushbu_p@hotmail.com
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This is a very useful video. Thanks for educating us. It would be a great help if you please make a tutorial about how to create a custom reference dataset. Thanks!
i waited for your videos for a long time 😊😊
Very helpful!!!Thank you very much!!😊😊
Your background information are very detail and meaningful. Thanks for making it easy for biologist! Cheers B-magician! The last 7 mins is not clear: Why do we need ontology term instead of label.main? Looking forward for next video on the actual output of singleR for results figures.
Hello thanks so much for these excellent videos. Could you kindly make a video on GSEA in r
Thank you for your great videos, could you please let us know how we can label our clusters manually...
very awesome video! is singleR capable for the sub cell type classification? or what is your recommendation for classify the sub cell types?
Wonderful work! Your tutorial is clear and efficient! How do we understand the metadata(com.res2$orig.results$DICE)$de.genes? This is a list, and for each cell type, there is a list of all other cell types as well. It's confusing.
Hi, doctor..I really appreciate your great content in teaching bioinfo.. Please I need a source for molecular docking and drug design expected to be as great as your content.. Thank you.
After 31:30, how do you write a column of the meta data that matches cell type to ontology ID?
Using Strategy 3 to annotate, the two reference files are still having different ont names. Thus as a result, "B cell" and ''B_cell" are still both present in the final UMAP. I don' t think this is what you want, is it?
can i have some plant related species too?