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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

The Spatial Transcriptomics Plot element

A Spatial Transcriptomics Plot () represents each barcode as one point, with its position determined by the spatial position within the tissue, optionally overlayed on an image of the corresponding tissue (figure 11.1). The spatial position of each barcode can be seen in the table () view.

Figure 11.1: A Spatial Transcriptomics Plot of the GSM7962129 data from the Gene Expression Omnibus repository. Top: Default view. Bottom: The image is fit to the tissue, and brightness, contrast and transparency are adjusted. The barcodes are colored using the expression of KRT10.

Using a Spatial Transcriptomics Plot, various aspects of the data can be visualized, cells can be manually annotated and various tools can be started using the information selected in the plot, see Single cell low-dimensional plots functionality for details.

When Overlay on image is checked, the tissue image, if available, is shown and the barcodes are displayed on top of it. If the image contains the fiducial markers, Fit to tissue can be used to clip the image to only show the tissue where barcodes have been detected. Using the sliders, the brightness and contrast of the image, as well as the transparency of the points, can be controlled.

Linking to a Dimensionality Reduction Plot

A Spatial Transcriptomics Plot can be linked to a Dimensionality Reduction Plot, such that the options and selections are mirrored in both plots. For example:

• The source of colors in the Spatial Transcriptomics Plot is controlled from the Side Panel of the Dimensionality Reduction Plot.
• Lasso selection of barcodes in one plot is reflected in the other.

To link the plots (figure 11.2):

• Open the Dimensionality Reduction Plot, if it is not already open. To visualize the plots side by side, use a split view, see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Arrange_views_in_View_Area.html for details.
• Associate the Dimensionality Reduction Plot to the Spatial Transcriptomics Plot by dragging the Dimensionality Reduction Plot into the 'Dimensionality reduction plot' Side Panel group of the Spatial Transcriptomics Plot. The association can be saved by saving the changes to the Spatial Transcriptomics Plot.
• Check Link to plot to link the two plots.

Figure 11.2: A Dimensionality Reduction Plot can be associated to a Spatial Transcriptomics Plot. Top left: Initial view. Top right: A plot has been dragged into the Side Panel and is now associated. Bottom left: An associated plot can be opened from the menu in the top right corner of the Side Panel group. Bottom right: The link is active.

On subsequent uses of the Spatial Transcriptomics Plot, the Dimensionality Reduction Plot can be opened from the Side Panel (figure 11.2).

An active link is indicated by a checkmark () in the Side Panel (figure 11.2). When there is an active link, most of the Side Panel groups for the Spatial Transcriptomics Plot are disabled and the coloring is based on the options chosen in the Dimensionality Reduction Plot (figure 11.3).

Figure 11.3: The source of colors in the Spatial Transcriptomics Plot is controlled from the Side Panel of the Dimensionality Reduction Plot. Lasso selections in either plot is reflected in both plots.

When the active link is disabled by unchecking Link to plot, the Side Panel groups for the Spatial Transcriptomics Plot are enabled again and the coloring is reverted to the state before the link was activated.

The link to the Dimensionality Reduction Plot can be manually refreshed by using the () button or toggling Link to plot. This needs to be done in a number of situations:

• The Dimensionality Reduction Plot was not opened prior to being associated to the Spatial Transcriptomics Plot.
• The current Dimensionality Reduction Plot is closed and the plot is then opened again.
• The Dimensionality Reduction Plot is closed. The Spatial Transcriptomics Plot will keep using the colors from the Dimensionality Reduction Plot until the link is disabled.

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