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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 Plain Text Table Expression Matrix
  • Export Peak Count Matrix
• Prepare Reads
  • Annotate Single Cell Reads
    • Read structure
    • Barcodes from names
    • Barcode correction
    • Sample name
    • 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
    • The output of QC for Single Cell
    • Choosing barcodes to retain
    • Cell calling
    • Automatic thresholds
    • Doublet calling
  • Demultiplex Parse Bio Samples
  • Normalize Single Cell Data
    • When is batch correction appropriate?
    • The output of Normalize Single Cell Data
    • The Normalize Single Cell Data algorithm
  • The Expression Matrix element
• Cell Type Classification
  • Browse QIAGEN Cell Ontology
  • Predict Cell Types
    • The output of Predict Cell Types
    • Cell type refinement
  • Train Cell Type Classifier
    • Features used for training and prediction
    • 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
    • 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
    • The output of Single Cell Velocity Analysis
    • The velocity estimation algorithm
  • Differential Velocity for Single Cell
  • Score Velocity Genes
    • The output of Score Velocity Genes
  • Create Phase Portrait Plot
  • Velocity analysis in workflows
  • The Velocity Matrix element
• Spatial Transcriptomics
  • The Spatial Transcriptomics Plot element
• Chromatin Accessibility
  • Single Cell ATAC-Seq Analysis
    • 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
  • The Peak Count Matrix element
• Immune Repertoire
  • Single Cell V(D)J-Seq Analysis
    • The report output from Single Cell V(D)J-Seq Analysis
    • The clonotype identification algorithm
  • Filter Cell Clonotypes
  • Combine Cell Clonotypes
  • Compare Cell Clonotypes
    • The output of Compare Cell Clonotypes
  • Convert Clonotypes to Cell Annotations
  • The Cell Clonotypes element
    • Primary and secondary clonotypes
    • Cell Clonotypes tables
    • Cell Clonotypes alignments
    • Cell Clonotypes Sankey plot
• 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
    • The output of Create Heat Map for Cell Abundance
  • Create Cell Annotations from Hashtags
  • The Cell Annotations element
  • The Cell Clusters element
• 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

Import Peak Count Matrix

Several formats can be imported into a Peak Count Matrix () using the following importers:

• Cell Ranger HDF5: Import Peak Count Matrix in Cell Ranger HDF5 format ();
• MEX: Import Peak Count Matrix in MEX format ();
• MEX archive: Import Peak Count Matrix in MEX format (archive) ().

The importers can be found here:

        Import () | Single Cell Data () | Import Peak Count Matrix ()

General options

Figure 4.6: The Cell Ranger Peak Count importer. The General options are common to all the peak matrix importers.

The following options are common to all peak matrix importers (figures 4.6 and 4.7):

• Gene track Positions in the imported data are matched with the provided track.

  Matching is used to:

  • View the Peak Count Matrix as a Track. For more information on tracks, see https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Tracks.html.
  • Identify nearby genes if these are not explicitly supplied.

• Cell format and Sample: How cells are identified. See Cell format in importers for more details.

  
  Figure 4.7: Additional options common to all the peak matrix importers.

• Nearby genes Nearby genes are determined in one of two ways:
  • By searching for nearby genes using the Gene track and an accompanying mRNA track
  • By supplying nearby genes in a selected tab-separated file (.tsv).

  The file must consist of either:

  • 6 columns: name of the chromosome prefixed with "chr" (e.g., "chr1"), start and end position of the peak, the name of the gene, distance and type of peak.
  • 4 columns: name of the chromosome together with start and end positions of the peak (e.g., "chr1:123-456"), the name of the gene, distance and type of peak.

  The first line must be column headers.

  The distance is the number of base positions from the start or end of the peak to the start or end of the gene, whichever is closest. It is signed and will be negative if the peak is before the gene.

  The type of the peak can be either "promoter" or "distal". Other values are ignored.

  If there are multiple nearby genes per peak, they can either be on separate lines or be grouped on one line, with gene name, distance and peak types separated by semi-colon.

• Transcription factors If enabled, transcription factors will be imported from the selected tab-separated bed file. Each line consists of the name of the chromosome (e.g., "chr1"), start and end positions of the peak, and the name of the transcription factor.

  If not enabled, the peak matrix will not have transcription factors.

The data to be imported may either consist of peak data only or it may be a mixture of peaks and gene expressions, as is the case for 10x Multiome files. In the latter case, the gene expressions must be imported into a separate Expression Matrix (see Import Expression Matrix).

MEX importer

The MEX importer requires three files to be supplied:

• Barcodes file A file with the extension .tsv and tab-separated columns, with one row per barcode. It can optionally contain a header. The barcodes are read from the first column. Empty lines are ignored.

  Use the Cell format option to control how the barcodes should be interpreted - for example if it also includes information about the sample.

• Feature or peak file This should be one of:
  • A feature file with extension .tsv and six tab-separated columns, with one row per feature or peak. These are relevant for mixtures of peaks and expressions, e.g. 10x Multiome. The columns are: identifier (e.g., "chr1:123-456"); name (same as identifier for peaks); type, e.g. "Gene Expression" or "Peaks"; chromosome (e.g., "chr1"); start and end position of the feature or peak. The file can optionally contain a header. Empty lines are ignored.
  • A peak file with extension .bed and three tab-separated columns: the chromosome, start and end position.
• Matrix file A file containing the expression with the extension .mtx in the Matrix Market Exchange Coordinate Format.

See https://math.nist.gov/MatrixMarket/formats.html for details of the Matrix Market Exchange Coordinate Format.

MEX archive importer

The MEX archive importer is provided for convenience. It accepts a .zip, .tar or .tar.gz archive file containing the files required by the MEX importer. In order to uniquely identify each file, these must have a specific name:

• Barcodes file must be named barcodes.tsv
• Feature or peak file must either be named features.tsv or peaks.bed
• Matrix file must be named matrix.mtx

Figure 4.8: Options for nearby genes and transcription factors for the MEX archive importer

The nearby genes and/or transcription factors can be passed in as separate files as is common to all the importers.

Alternatively, they can be included in the archive file. Then that should be indicated with checkbox "Archive has peak annotations" respectively "Archive has peak-motif associations". The file names must match a specific pattern:

• Nearby genes file must end with peak_annotation.tsv
• Transcription factor file must end with peak_motif_mapping.bed

This can be relevant for importing an archive produced by the peak matrix exporter using compression (see Export Peak Count Matrix). It may also be necessary when passing multiple files to a batching or iterating workflow (see Chromatin Accessibility and Expression Analysis from Matrix).

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