Image source: https://web.genewiz.com/single-cell-faq

• Aim of QC is …

  • To remove undetected genes
  • To remove empty droplets
  • To remove droplets with dead cells
  • To remove Doublet/multiplet
  • Ultimately To filter the data to only include true cells that are of high quality

• Above is achieved by …

  • Applying hard cut-off or adaptive cut-off on …
    • Number of genes detected per cell
    • Percent of mitochondrial genes per cell
    • Number of UMIs/transcripts detected per cell

Bioconductor R packages:

• scran: Collection functions for interpretation of single-cell RNA-seq data
• scater: For focus on quality control and visualization.
• DropletUtils: Handling single-cell (RNA-seq) data from droplet technologies such as 10X Genomics

Orchestrating Single-Cell Analysis with Bioconductor Robert Amezquita, Aaron Lun, Stephanie Hicks, Raphael Gottardo

http://bioconductor.org/books/release/OSCA/

• CellRanger outputs: gives two output folders raw and filtered

• Each folder has three zipped files

  • features.tsv.gz, barcodes.tsv.gz and matrix.mtx.gz
  • raw_feature_bc_matrix
    • All valid barcodes from GEMs captured in the data
    • Contains about half a million to a million barcodes
    • Most barcodes do not actually contain cells
  • filtered_feature_bc_matrix
    • Excludes barcodes that correspond to this background
    • Contains valid cells according to 10x cell calling algorithm
    • Contains 100s to 1000s of barcodes

To access counts from sce object: counts(sce)

To access gene metadata from sce object: rowData(sce)

To access cell metadata from sce object: colData(sce)

• Selecting appropriate thresholds for filtering, so that high quality cells are kept without removing biologically relevant cell types
  • Differentiating poor quality cells from less complex ones
    
  • Differentiating transcriptionally active cell types from multiplets/doublets
  • Distinguishing dead cells from those cells that express a high proportion of mitochorial genome

• Ensure that you know what types of cells you expect to be present before performing the QC.
  
• Are you expecting to find low complexity cells in your sample or cells with higher levels of mitochondrial expression?
• When assessing the quality of our data, we must take this biology into consideration