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 enabled during execution:
- 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.
Choose either one or more Expression Matrix () / () and Peak Count Matrix () or Select files for import and select the formats that are compatible with the selected inputs.
Read more about import options in Importing data.
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