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• Introduction
  • The concept of CLC Single Cell Analysis Module
  • Contact information
  • System requirements
  • Installing modules
    • Licensing modules
    • Uninstalling modules
  • Installing server extensions
    • Licensing server extensions
• Reference data management
  • QIAGEN Sets
• Running tools and workflows
• Data import
  • Import Cell Annotations
  • Import Cell Clusters
  • Import Cell Clonotypes
  • Import Expression Matrix
    • HDF5 formats
    • Other formats
  • Import Peak Count Matrix
  • Import Space Ranger
  • Cell format in importers
  • Import Immune Reference Segments
    • IMSEQ
    • IMGT
    • Output from Import Immune Reference Segments
• Data export
  • Export Cell Ranger HDF5 Expression Matrix
  • Export AnnData Expression Matrix
  • Export h5Seurat Expression Matrix
  • Export Loom Expression Matrix
  • Export MEX Expression Matrix
  • Export TXT Expression Matrix
  • Export Peak Count Matrix
• Prepare Reads
  • Annotate Single Cell Reads
    • Setting the sample name
    • Interpreting the output of Annotate Single Cell Reads
• Creating a Gene Expression Matrix
  • Single Cell RNA-Seq Analysis
    • The Single Cell RNA-Seq Analysis report
    • The Single Cell RNA-Seq Analysis algorithm
  • QC for Single Cell
    • Empty droplets filter
    • Count-based and extra-chromosomal filters
    • Doublets filter
    • Interpreting the output of QC for Single Cell
    • Choosing barcodes to retain
    • The cell calling algorithm
    • The doublet calling algorithm
  • Normalize Single Cell Data
    • When is batch correction appropriate?
    • Interpreting the output of Normalize Single Cell Data
    • The Normalize Single Cell Data algorithm
• Cell Type Classification
  • Browse QIAGEN Cell Ontology
  • Predict Cell Types
    • Interpreting the output of Predict Cell Types
    • Cell type refinement
  • Train Cell Type Classifier
    • Features used for training and prediction
    • Interpreting the output of Train Cell Type Classifier
    • SVMs for cell type classification
  • Update Cell Type Classifier
  • The Cell Type Classifier element
• Expression Analysis
  • Differential Expression for Single Cell
    • Interpreting the output of Differential Expression for Single Cell
    • The differential expression algorithm
  • Create Expression Plot
    • The Heat Map output of Create Expression Plot
    • The Dot Plot output of Create Expression Plot
    • The Violin Plot output of Create Expression Plot
• Velocity Analysis
  • Single Cell Velocity Analysis
    • Interpreting the output of Single Cell Velocity Analysis
    • The velocity estimation algorithm
  • Differential Velocity for Single Cell
  • Score Velocity Genes
    • Interpreting the output of Score Velocity Genes
  • Create Phase Portrait Plot
  • Velocity analysis in workflows
• Spatial Transcriptomics
  • The Spatial Transcriptomics Plot element
• Chromatin Accessibility
  • Single Cell ATAC-Seq Analysis
    • Interpreting the output of Single Cell ATAC-Seq Analysis
    • The report output from Single Cell ATAC-Seq Analysis
    • The Single Cell ATAC-Seq Analysis algorithm
  • Split Read Mapping by Cell
  • Differential Accessibility for Single Cell
    • The differential accessibility algorithm
• Immune Repertoire
  • Single Cell V(D)J-Seq Analysis
    • The report output from Single Cell V(D)J-Seq Analysis
    • The clonotype identification algorithm
  • The Cell Clonotypes element
    • Primary and secondary clonotypes
    • Cell Clonotypes tables
    • Cell Clonotypes alignments
    • Cell Clonotypes Sankey plot
  • Filter Cell Clonotypes
  • Combine Cell Clonotypes
  • Compare Cell Clonotypes
    • Interpreting the output of Compare Cell Clonotypes
  • Convert Clonotypes to Cell Annotations
• Noise reduction through feature selection and dimensionality reduction
  • Feature selection and dimensionality reduction
    • Calculation of estimated biological variation
• Cell Annotation
  • Cluster Single Cell Data
    • The Cluster Single Cell Data algorithm
  • Create Heat Map for Cell Abundance
    • Interpreting the output of Create Heat Map for Cell Abundance
  • Create Cell Annotations from Hashtags
• Dimensionality reduction
  • UMAP for Single Cell
  • tSNE for Single Cell
• Single cell low-dimensional plots functionality
  • Manual annotation
  • Visualizing different types of matrices
  • Create Subset
  • Extract to Table
  • Launching of Create Expression Plot
  • Launching of Create Heat Map for Cell Abundance
  • Launching of Differential Accessibility for Single Cell
  • Launching of Differential Expression for Single Cell
  • Launching of Differential Velocity for Single Cell
  • Launching of Score Velocity Genes
• Utility tools
  • Combine Cell Annotations
  • Update Cell Annotations
  • Convert Metadata to Cell Annotations
  • Combine Cell Clusters
  • Update Cell Clusters
  • Add Information to Plot
  • Update Single Cell Sample Name
• Single cell template workflows from reads
  • Expression Analysis from Reads
    • Configuring the batch units for Expression Analysis from Reads
    • Output from Expression Analysis from Reads
  • Chromatin Accessibility Analysis from Reads
    • Configuring the batch units for Chromatin Accessibility Analysis from Reads
    • Output from Chromatin Accessibility Analysis from Reads
  • Chromatin Accessibility and Expression Analysis from Reads
    • Configuring the batch units for Chromatin Accessibility and Expression Analysis from Reads
    • Output from Chromatin Accessibility and Expression Analysis from Reads
    • Importing reads
  • Immune Repertoire Analysis from Reads (10xV(D)J)
    • Output from Immune Repertoire Analysis from Reads (10xV(D)J)
  • Immune Repertoire and Expression Analysis from Reads (10xV(D)J)
    • Configuring the batch units for Immune Repertoire and Expression Analysis from Reads (10xV(D)J)
    • Output from Immune Repertoire and Expression Analysis from Reads (10xV(D)J)
• Single cell template workflows from imported data
  • Expression Analysis from Matrix
    • Output from Expression Analysis from Matrix
  • Chromatin Accessibility and Expression Analysis from Matrix
    • Output of Chromatin Accessibility and Expression Analysis from Matrix
  • Immune Repertoire and Expression Analysis from Clonotypes and Matrix
    • Output from Immune Repertoire and Expression Analysis from Clonotypes and Matrix
  • Importing data
• Bibliography

Cell Clonotypes Sankey plot

The Sankey plot view ()

• shows how the segments of different types form the clonotypes for a given chain, when "Show column per" is set to "Grouping property" in the Side Panel (figure 13.8);
• compares clonotypes frequencies across samples, when "Show column per" is set to "Sample" in the Side Panel (figure 13.10). This option is available only for Cell Clonotypes containing more than one sample.

Note that only primary clonotypes (see Primary and secondary clonotypes) are included in the Sankey plot. For visualizing secondary clonotypes, run first Filter Cell Clonotypes with `Multiple clonotypes' set to `Retain secondary', see Filter Cell Clonotypes for details.

To keep the plot size manageable, it is recommended to filter the clonotypes using the Filter Cell Clonotypes tool.

Grouping property

Figure 13.8: Sankey plot for the TRA and TRB chains showing the V and J segments. Numbers in brackets show the total barcode count. Flows show how many barcodes have clonotypes with the specific chain and segment combinations. The plot is restricted to showing only the most common 5 TRA-V segment. The box for TRA-J-45 contains a white region because there are barcodes with TRA-J-45 that have a TRA-V segment that is different than those present in the plot.

For each selected segment type, the plot has a column that contains boxes for each segment. The box height reflects the total number of cells containing clonotypes with the given segment. The boxes are connected with flows. The color of a flow indicates the element where the flow starts. "Flows start at" can be used to change the start column, by default the leftmost. "Show continuous flows" controls the type of the flows:

• If not ticked, there are flows between boxes in consecutive columns for clonotypes having segments corresponding to the boxes. The height of the flow indicates the total number of cells for these clonotypes.
• If ticked, the flows start from the fixed column defined by "Flows start at". When the flow starts at the leftmost column, flows between boxes in the first two columns reflect clonotypes with segments corresponding to the two boxes. Flows between boxes in the second and third column reflect clonotypes corresponding to the boxes in both the first, second and third column, and so on.

"Show continuous flows" has no effect when there are less than three columns.

Boxes can be removed from the plot by using the options under "Filtering" in the Side Panel (figure 13.8). The plot will show only boxes for the selected segments and the boxes to which the selected segments have a flow. If multiple filters are used, boxes are subject to all the restrictions (figure 13.9).

The columns and their order can be changed by using the options under "Group by" in the Side Panel. The CDR3 amino acid sequences can also be shown, see figure 13.9.

Figure 13.9: Sankey plot for the TRA and TRB chains showing the V(D)JC segments and CDR3. The plot is filtered to show only the most common 5 TRA and TRB V(D)JC segments. Note that only 4 boxes for TRA-VJC and TRB-VDJC are present in the plot, because there are no barcodes containing both of the missing TRA-VJC and TRB-VDJC. Clonotypes can have CDR3s that are out of frame and are hence missing a CDR3 AA. These are shown in the None box.

Sample

Figure 13.10: Sankey plot for the TRA and TRB chains showing the clonotypes count with specific V and J segments, compared across samples. Number in brackets show the total barcode count.

For each selected sample, the plot has a column that contains boxes for each group of clonotypes (hereafter referred to as simply clonotypes) with the selected properties. The properties, such as the segment type or the CDR3 amino acid sequence, are selected from the Side Panel under "Group by".

The height of a box indicates the frequency of the clonotypes in the sample. The frequency is defined as the number of barcodes with the specific clonotype, divided by the total number of barcodes found in the sample.

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