Analysis of single cell expression data using the R package, Seurat by Satija Lab
This analysis is an implementation of the Seurat tutorial available at https://satijalab.org/seurat/v3.0/pbmc3k_tutorial.html. You may also use the 10X-PBMC3k Healthy Donor dataset mentioned in the tutorial.
Dataset: 10X-PBMC10k Healthy Donor dataset ( https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.0.0/pbmc_10k_v3)
Single Cell Gene Expression Dataset by Cell Ranger 3.0.0
Peripheral blood mononuclear cells (PBMCs) from a healthy donor (the same cells were used to generate pbmc_1k_v2, pbmc_10k_v3). PBMCs are primary cells with relatively small amounts of RNA (~1pg RNA/cell).
11,769 cells detected
Sequenced on Illumina NovaSeq with approximately 54,000 reads per cell
28bp read1 (16bp Chromium barcode and 12bp UMI), 91bp read2 (transcript), and 8bp I7 sample barcode
run with --expect-cells=10000
R packages: i) Seurat ii) dplyr iii) ggplot2 iv) gridExtra v) reticulate vi) umap vii) magrittr
To know more about the algorithms used in Seurat, please refer to https://www.biorxiv.org/content/biorxiv/early/2018/11/02/460147.full.pdf