Code utilized for analysis of scRNA-seq data in CD27 Agonism Enhances Long-Lived CD4 T Cell Vaccine Responses Critical for Anti-Tumor Immunity

Description of workflow

Following processing steps using 10X software multi-pipeline, scRNA-seq data for all samples were collated into a single Seurat object for QC and integration using ‘aCD27_integration_and_QC.R’. This script utilized ‘calculate_sample_experiment_entropy.R’ and  ‘make_entropy_plots.R’  to assess cell type and integration performance. Next, for visualization and cell type assignment, relevant marker and immune biology genes were loaded with ‘load_immune_markers.R’. To establish doublet-free well-annotated cells,  we filtered clusters for discordant marker gene expression using genes loaded with ‘load_immune_gene_filters.R’. Scripts for filtering each relevant immune type included: ‘sort_and_filter_mitotic.R’, ‘filter_cells_by_gene_expression.R’, and ‘sort_Tcells.R’. Finally, to facilitate consistent visualization, orderings for cell types, classes, and clusters were specificied in ‘load_group_orders.R’.

Next analysis of gene expression differences across experimental arms in specific cell types were analyzed in manuscript preparation were analyzed in ‘aCD27_GEX_analysis.R’ . Again, to make consistent ordering for figures, ‘load_group_orders.R’  is sourced.  ‘load_immune_markers.R’ provides key immune marker genes for relevant plots. DE expression comparisons across experimental groups was facilitated by function loaded in ‘useful_functions.R’.

Finally, clonotype analysis and relevant figure generation was performed using code found in ‘aCD27_clonotype_analysis.R’.

For clarity the user facing scripts are listed in bold below and the scripts required to run those with sub-functions and tools are listed beneath the relevant user-facing script. Users will need to alter paths and download relevant software before running in their local environment. 

List of scripts

aCD27_integration_and_QC.R

    calculate_sample_experiment_entropy.R

    make_entropy_plots.R

    load_immune_markers.R

    load_immune_gene_filters.R

    sort_and_filter_mitotic.R

    filter_cells_by_gene_expression.R

    sort_Tcells.R

    load_group_orders.R

aCD27_GEX_analysis.R

     load_group_orders.R

     load_immune_markers.R

     useful_functions.R"

aCD27_clonotype_analysis.R