Single-cell RNA-seq analysis of public 10x data

1. Download data

scRNA-seq data were obtained from the public 10× genomics application note: A New Way of Exploring Immunity (www.10xgenomics.com/resources/application-notes/a-new-way-of-exploring-immunity-linking-highly-multiplexedantigen-recognition-to-immune-repertoire-and-phenotype/).

• donor 1
  $ curl -O https://cf.10xgenomics.com/samples/cell-vdj/3.0.2/vdj_v1_hs_aggregated_donor1/vdj_v1_hs_aggregated_donor1_filtered_feature_bc_matrix.tar.gz

• donor 4
  $ curl -O https://cf.10xgenomics.com/samples/cell-vdj/3.0.2/vdj_v1_hs_aggregated_donor4/vdj_v1_hs_aggregated_donor4_filtered_feature_bc_matrix.tar.gz

2. Normalize and integrate

CD8+ T cell gene expression data from both healthy donors was then normalized with SCTransform and integrated with Seurat v3 using the script integrate_d1_d4.R available on GitHub: https://github.com/Jb-Gorin/Sekine-et-al.-2020/blob/master/integrate_d1_d4.R

3. DEG

Tox+ (1909) and Tcf+ (9430) cells were identified, and differentially expressed genes (DEGs) were determined using DESeq2 using the script DEG_Tox_Tcf7.R available on GitHub: https://github.com/Jb-Gorin/Sekine-et-al.-2020/blob/master/DEG_Tox_Tcf7.R