Automatic cell-annotation for single-cell RNA-Seq data: A detailed SingleR tutorial (PART 2)
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-annotation for single-...
▸ Link to Data:
https://www.10xgenomics.com/resources...
▸ Link to Code:
https://github.com/kpatel427/YouTubeT...
▸ Resources/Vignettes:
1. https://www.nature.com/articles/s4159...
2. http://bioconductor.org/books/release...
3. http://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:
https://www.buymeacoffee.com/bioinfor...
To get in touch:
Website: https://bioinformagician.org/
Github: https://github.com/kpatel427
Email: [email protected]
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