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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

Update Cell Clusters

The Update Cell Clusters tool takes one Cell Clusters () element as input and outputs a new Cell Clusters () element containing updated categories and/or clusters.

The tool can be found in the Toolbox here:

        Toolbox | Single Cell Analysis () | Utility Tools () | Update Cell Clusters ()

In the first wizard step `Update categories', the following options can be adjusted:

• Remove categories. The selected categories are removed.
• Remove all empty categories. Categories without any clusters are removed. Categories are also removed if empty after removal of clusters (see below).
• Rename categories. One or more categories are renamed. The Add button can be used to add additional categories to be renamed. Note that multiple categories cannot be renamed to the same name.
• Rename all categories. All categories are renamed according to the given pattern. This can be used for both prepending and appending to the name. E.g., if set to `MyPrefix {categoryName} MySuffix', a category `MyCategory' will be renamed to `MyPrefix MyCategory MySuffix'. This is done after the changes specified by Rename categories.

In the next wizard step `Update clusters', the clusters can be updated. The following options can be adjusted:

• Update clusters for. The updates can be applied to:
  • No categories. Skip updating clusters.
  • All categories. Update the clusters for all categories.
  • Selected category. Update the clusters only for the category selected in Update clusters for category.
• Remove clusters. The selected clusters are removed.
• Remove all empty clusters. Clusters with no cells are removed.
• Rename clusters. One or more clusters are renamed. The Add button can be used to add additional clusters to be renamed.
• Map clusters to QIAGEN Cell Ontology. When this is enabled, clusters will be translated, if possible, to the QIAGEN Cell Ontology (see The QIAGEN Cell Ontology). The translation attempts to match each cluster with a QIAGEN cell type based on the name and known synonyms. For example, `alveolar epithelial cells' are also called `pneumocytes'. If this option is selected, the `alveolar epithelial cells' cluster, if present, will be named `pneumocytes'. This option can be useful when standardizing clusters from different sources. It is especially recommended if clusters will be used to extend a QIAGEN Cell Type Classifier using the Train Cell Type Classifier tool (Train Cell Type Classifier).

If two distinct clusters are given the same name, they are combined into one. This can happen if:

• A cluster is renamed to an existing name.
• Two clusters are renamed to the same name.
• Two cluster names are synonyms for the same QIAGEN cell type and clusters are mapped to the ontology.

The options above can be mixed and matched to obtain the desired output. For example, a cluster can be first renamed and then the new name can be mapped to the ontology.

The Update Cell Clusters tool can also be started from the different views of the Cell Clusters () element, with dialogs automatically filled in with relevant selections:

• From the clusters table view ():
  • Clusters can be removed or renamed from the right-click menu. Multiple rows can be selected before using the right-click menu.
  • A category can be removed or renamed using the Remove and Rename buttons from the Side Panel.
• From the cell-level view (), the category over which the mouse hovers can be removed or renamed from the right-click menu.

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