Published September 10, 2020 | Version 1
Dataset Open

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

  • 1. Genome Institute of Singapore (GIS), A*Star

Description

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


 

Files

CITESeq_Scanpy.ipynb

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