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 <br>