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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 format in importers

All importers in the CLC Single Cell Analysis Module import information about cells. Cells are identified by a combination of their barcode, e.g. "AAGCT", and their sample name.

Importers share the following common options:

• Cell format. This option allows the barcode and the sample name to be extracted separately from the name of the cell. By default, the name of the cell is used as the barcode. For matrix importers, the sample name is set to the name of the imported file. For the remaining importers, the sample name has to be provided through one of multiple options.

  The cell format is specified by using a mixture of keywords (see figure 4.7) and text, see table 4.1 and figure 4.8 for examples.

  
  Figure 4.7: Keywords that can be used to specify how to extract the barcode and sample name for a cell.

  
  

  Table 4.1: Examples of cell formats and the resulting samples and barcodes. * The sample is obtained either from the name of the imported file, for matrices, or from the other sample options. ** This example assumes a matrix file named "demo.h5".

  Cell format Name of the cell Sample   Barcode {barcode}-1 AAGCT-1 - * AAGCT {sample}-{barcode} demo-AAGCT demo   AAGCT {sample}-{barcode} demo-AAGCT demo   AAGCT {sample}-{barcode} de-mo-AAGCT de   mo-AAGCT {sample}-{barcode:trailing} de-mo-AAGCT de-mo   AAGCT {barcode:1}-{sample}-{barcode:2} AA-demo-GCT demo   AAGCT {barcode}-{sampleSuffix} AAGCT-1 demo-1 ** AAGCT

  
  

  
  Figure 4.8: The top panel shows the results of importing a matrix file with Cell format = {barcode}. After import, the sample name is the name of the file that was imported, and the barcode is the entire name of the cell. In the bottom panel, Cell format = SRX41800{sample}_filter.{barcode}. Here, the sample name and the barcode are extracted from the name of the cell, and other parts of the name are discarded.

• Sample (Optional). This can be used for specifying a custom sample name. It should only be used when the file contains just one sample. It overrides the default sample name.

  This is relevant e.g. when jointly analyzing an imported Expression Matrix and Peak Count Matrix, where cells must have the same sample name.

Importers contain a Preview cells section showing the parsing of cell names into sample and barcode, as shown in figure 4.9.

Figure 4.9: Previewing how the cell name (input barcode) resolves to sample and barcode.

This can be helpful for ensuring the provided cell format matches the input. Figure 4.10 shows an example where the sample and barcode have clearly been swapped, while in figure 4.11, the sample and barcode cannot be identified for one of the cells, because the cell name does not match the cell pattern.

Figure 4.10: Preview where the sample and barcode have been swapped

Figure 4.11: Preview where a cell does not match the pattern. The tooltip contains a detailed error message.

If the configuration in the wizard is invalid, the preview may fail to determine the sample and/or barcode for all cells, as shown in figure 4.12.

Figure 4.12: Preview where the sample cannot be determined. The tooltip indicated why and it will typically match a validation error from the wizard. Here, the sample is specified in two ways. The barcode can still be determined.

The preview can be disabled if not needed. This is useful for input files that are large, where generating the preview may take some time.

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