Seurat is an R package frequently employed for the QC, analysis, and exploration of single-cell RNA-seq data. Here, I have explored several example datasets to gain familiarity analysing high-dimensional transcriptomics data.
This provided experience working with these types of data and allowed me to support the subsequent SenPred ML classification project. I also used it as a chance to gain familiarity with R markdown and using code chunks.
Methods
- Quality control / Normalisation
- Dimensionality reduction
- Clustering / Visualisation
- Differential expression analysis
- Integration
Outputs
- Identified cell clusters representing different types.
- Visualised clusters and marker genes.
- Detected differential gene expression.
- Integrated multiple datasets.
