Chromatin Accessibility and Expression Analysis from Matrix
The workflow Chromatin Accessibility and Expression Analysis from Matrix takes a pair of an Expression Matrix (
) / (
) and a Peak Count Matrix (
) as input to jointly analyze scRNA-Seq and scATAC-Seq data originating from the same sample or samples.
The expression matrix is analyzed as described in Expression Analysis from Matrix. Clustering and dimensionality reduction are performed using both expression and peak matrices.
The workflow allows for a combined analysis to produce:
- a single normalized Expression Matrix ();
- a Dimensionality Reduction Plot (
) associated with the automated clusters, predicted cell types and additional cell annotations;
- a Heat Map (
), a Dot Plot (
), and a Violin Plot (
) with the predicted cell types as cell groups;
- a Cell Abundance Heat Map () with the automated clusters and predicted cell types as cell groups.
- If velocity analysis is run:
- a Phase Portrait Plot (
) with per gene information on the velocity dynamics;
- a Velocity Genes Scores (
) element allowing identification of velocity genes driving the dynamics.
- a Phase Portrait Plot (
The workflow can be found here:
Template Workflows | Single Cell Workflows (
) | From Imported Data (
) | Chromatin Accessibility and Expression Analysis from Matrix (
)
If you are connected to a CLC Server via the CLC Workbench, you will be asked where you would like to run the analysis. We recommend that you run the analysis on a CLC Server when possible.
Using a Fork element, the workflow offers the option to run velocity analysis. To enable this, set Velocity Analysis to Run in the Specify Workflow Path wizard step. See https://resources.qiagenbioinformatics.com/manuals/clcgenomics/current/index.php?manual=Fork.html for details.
Choose either one or more Expression Matrix () / () and Peak Count Matrix () or Select files for on-the-fly import and select the format that is compatible with the selected inputs.
Read more about import options in On-the-fly import in workflows.
Note that the sample in the inputs must be the same for cells originating from the same sample. This can be achieved in different ways, depending on how the elements were generated:
- If the input elements were generated in the CLC Single Cell Analysis Module, the sample name can be set when running Annotate Single Cell Reads.
- If the input elements are imported, the sample name can be set during import through the Cell format or Sample options, see Cell format in importers.
- The tool Update Single Cell Sample Name (
) can be used for updating the sample name in either input element, see Update Single Cell Sample Name.
The workflow offers a number of options. Note that not all parameters can be configured. Open parameters indicate places where customization may be necessary for different samples, but default settings are suitable in most cases.
The workflow can be run using Single Cell hg38 (Ensembl) or Single Cell Mouse (Ensembl) reference data sets (see Reference data management).
|
Note: Reference data elements cannot be configured during workflow execution. If other elements than those provided in the default reference data sets are needed, a custom reference data set can be used, see
https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Custom_Sets.html.
When creating custom reference data sets, the chosen gene track needs to match the gene annotations used for training the provided Cell Type Classifier ( |
) (see
Subsections