Robust clustering and interpretation of scRNA-seq data using reference component analysis

Datasets and Code accompanying the new release of RCA, RCA2. The R-package for RCA2 is available at GitHub: https://github.com/prabhakarlab/RCAv2/

The datasets included here are:

• Datasets required for a characterization of batch effects:
  • merged_rna_seurat.rds
  • de_list.rds
  • mergedRCAObj.rds
  • merged_rna_integrated.rds
• 10X_PBMCs.RDS: Processed 10X PBMC data RCA2 object (10X PBMC example data sets )
• NBM_RDS_Files.zip: Several RDS files containing RCA2 object of Normal Bone Marrow (NBM) data, umap coordinates, doublet finder results and metadata information (Normal Bone Marrow use case)
• Dataset used for the Covid19 example: 
  • blish_covid.seu.rds
  • rownames_of_glocal_projection_immune_cells.txt
  • Blish_RCA_no_QC_filtering_project_to_multiple_panels.rds
• Data sets used to outline the ability of supervised clustering to detect disease states:
  • 809653.seurat.rds
  • blish_covid.seu.rds
• Performance benchmarking results:
  • Memory_consumption.txt
  • rca_time_list.rds
• ScanPY input files:
  • input_data.zip

The R script provides R code to regenerate the main paper Figures 2 to 7 modulo some visual modifications performed in Inkscape.

Provided R scripts are:

• ComputePairWiseDE_v2.R (Required code for pairwise DE computation)
• RCA_Figure_Reproduction.R

Provided python Code for Scanpy analysis:

• RA_Scanpy.ipynb
• CITESeq_Scanpy.ipynb