Explore advanced techniques for cell type annotation in single-cell RNA-Seq data using multiple reference datasets in this comprehensive video tutorial. Learn various strategies for annotation, including using combined references, comparing scores across references, and employing harmonized labels. Discover how to fetch reference datasets from the celldex package, visualize results in UMAP plots, and create diagnostic heatmaps. Gain insights into the strengths and pitfalls of each approach, understand how to handle label inconsistencies across references, and learn to map cell ontology terms to labels. Follow along with practical demonstrations using SingleR and delve into the intricacies of cell type annotation to enhance your bioinformatics skills.
Automatic Cell Annotation for Single-Cell RNA-Seq Data - Multiple Reference Strategies in SingleR - Part 2
Overview
Syllabus
Intro
Strategies for using multiple reference datasets for annotation
Study design and goal of the analysis
Fetching 2 reference datasets from celldex package
Annotation strategy 1: Using a combined reference
Visualize results of strategy 1 in a UMAP
Annotation strategy 2: Comparing scores across references
Which reference scored the best for which label?
How to get the markers for each label from individual references?
Combined diagnostic heatmap
Lack of consistency in labels across references
Annotation strategy 3: Using harmonized labels
How to map cell ontology terms to labels?
Taught by
bioinformagician
