Integrative analysis of human SMART-seq and 10x single-cell gene expression data. How do the methodologies compare in defining cell types, and how can we use single-cell data for case-control analyses?
Main idea: perform integrative analysis of two human neocortical single-cell datasets, which will lead into an analysis of cell type-specific differential gene expression between individuals with dementia and controls.
Key questions:
- How does gene expression compare between cell types defined by SMART-seq vs. those defined by 10x sequencing?
- Are certain cell types better defined by one method relative to the other?
- How does cell type-specific gene expression change in the context of dementia?
- What types of genes are most affected by the condition within a given cell type?
What datasets are available to help answer these questions? Allen Institute for Brain Sciences Cell Types database
Transcriptomics TAs: Mel Davie, Derek Howard
Seurat tutorials:
- Dataset integration workflow
- Differential expression analysis
- Data visualization methods
- Cell type annotation
Pseudobulk differential expression tutorial
Day 1: Intro to single-cell RNAseq analysis, R, and Seurat
Day 2: Intro to differential expression, cell type identification & visualizations
Day 3: Dataset integration & automated cell type annotation
Day 4: Case-control differential expression with pseudobulks
Day 5: Spatial biology talks @ SickKids & final presentation!