Clustering, annotation and trajectory interference tools for scRNA-seq data: A quick guide
Useful tutorials and studies:
- Decoding human fetal liver haematopoiesis – scRNA-seq study on fetal liver
- Developmental cell programs are co-opted in inflammatory skin disease – scRNA-seq study on human skin
- Prenatal development of human immunity – review on developmental immunity
- A cell atlas of human thymic development defines T cell repertoire formation – scRNA-seq study on thymus
- Scanpy tutorial – for analysis of scRNA-seq data using Scanpy package in Python
- Seurat tutorial – for analysis of scRNA-seq data using Seurat package in R
- Automated methods for cell type annotation on scRNA-seq data – paper describing automated annotation techniques
- Diffusion maps for high-dimensional single-cell analysis of differentiation data – paper on diffusion map technique
- Computational approaches for interpreting scRNA‐seq data – a paper showing scRNA-seq analysis workflow, including different trajectory inference techniques