Chromatin Accessibility and Expression Analysis from Reads

The workflow Chromatin Accessibility and Expression Analysis from Reads takes 10x Multiome ATAC and gene expression (GEX) reads as input and starts by annotating them with cell barcode and UMI, followed by trimming.

During the annotation the barcodes from the ATAC reads are translated to barcodes that match the cell barcodes of GEX reads. The ATAC reads are then mapped and, in case of multiple samples, combined into one before producing one Peak Count Matrix (Image peak_count_matrix_16_n_p).

The GEX reads are analyzed as described in Expression Analysis from Reads. Clustering and dimensionality reduction are performed using both expression and peak matrices.

The workflow allows for a combined analysis of multiple samples to produce:

The workflow can be found here:

        Template Workflows | Single Cell Workflows (Image sc_workflow_folder_open_16_n_p) | From Reads (Image sc_wf_from_reads_folder_open_16_n_p) | Chromatin Accessibility and Expression Analysis from Reads (Image sc_atac_rna_reads_16_n_p)

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.

You can choose either one or more Sequence lists or Select files for import and select FASTQ files for importing.

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 (Image cell_type_classifier_16_n_p) (see Features used for training and prediction).

The workflow allows the analysis of multiple samples. Metadata must always be specified for configuring which inputs belong to which sample. In addition to group the input, metadata is converted to cell annotations and can be used for coloring the cells in the Dimensionality Reduction Plot.

For more details on configuring workflow execution with metadata, see https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Running_workflows_in_batch_mode.html. Make sure to inspect the batch overview to check that the analysis will be performed correctly.



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