Render

This module performs the extraction of useful metrics, and uses them to generate a series of summary plots, in PNG, HTML or PDF format.

Usage

The minimal command is cl render --input-path <PATH> --output-path <PATH>, where input-path is the path to the AVITI data folder and output-path is the directory where the plots will be placed.

Options

  • --stats-json: Path to the cell2stats 'RunStats.json' file. Required only if different from <INPUT_PATH>/RunStats.json.
  • --panel-json: Path to the cell2stats 'Panel.json' file. Required only if different from <INPUT_PATH>/Panel.json.
  • --raw-parquet: Path to the cell2stats 'RawCellStats.parquet' file. Required only if different from <INPUT_PATH>/RawCellStats.parquet.
  • --wells: Comma-separated list of wells to include in the analysis. By default, all wells will be used.
  • --batches: Comma-separated list of batches to include in the analysis. By default, all batches will be used.
  • --plot-list: Comma-separated list of plots to generate. Accepted values include 'All', 'BatchWell', 'Well', 'Count', 'Correlation', 'UMAP'. Default: All.
  • --format: It can be one of 'html', 'png' or 'pdf'. Default is 'png'.

Outputs

Barcoding performance metrics

Groups of barcodes are sequenced in serial batches, where each batch is defined by a specific sequencing primer.

Metric Description Expected Value
PercentAssignedReads Of all polonies, percentage assigned to an expected barcode > 70%
PercentMismatch Of all polonies assigned to a barcode, percentage assigned with a mismatch < 35%
  • PercentAssignedReads.*: Percentage of assigned reads.
  • PercentMismatch.*: Percentage of

Cell segmentation performance metrics

Cell segmentation is performed based on the cell paint images for the cell membrane, nucleus and actin. The metrics below summarize the results of the segmentation process for each well in the flowcell.

Metric Description Expected Value
PercentConfluency Fraction of well area occupied by cells 25-50% (variable based on cell seeding)
CellCount Number of objects detected during segmentation >10,000 (variable based on cell seeding)
MedianCellDiameter Approximate median diameter of cells in microns ~35 um
PercentNucleatedCells Fraction of cells with segmented nucleus > 97%
  • PercentConfluency.*: Wells confluency.
  • CellCount.*: Cell counts.
  • MedianCellDiameter.*: Cell diameters.

Cell assignment metrics

After barcoding and cell segmentation is complete, individual barcodes are assigned to cells. The metrics below summarize this process.

Metric Description Expected Value
AssignedCountsPerMM2 Number of assigned polonies per mm2 of cell area ~150,000 (protein), 200,000-300,000 (RNA)
  • AssignedCountsPerMM2.*: Counts per mm^2.

Correlation metrics

For each pair of wells, we can calculate the correlation of log-transformed average counts as a measure of reproducibility. For both RNA and protein data types, replicates wells should have R2 > 0.95.

  • RNADistCorr.*: RNA counts distance correlation matrix.
  • ProteinDistCorr.*: Protein counts distance correlation matrix.

UMAP projection and cell state

The single-cell data can be used to generate a UMAP projection. Across the entire flowcell, the UMAP projection should separate the data into two well-defined clusters, with the two different cell types comprising each cluster. Within each cluster, a circular pattern should exist, corresponding to the annotated cell state.

  • WellLabelUMAP.*: UMAP coloured by labels.
  • phaseUMAP.*: UMAP coloured by cell state.