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Low-quality cells can be filtered out during the spatial data analysis and will not be viewed on the tissue image. A few examples of low-quality cells are doublets, cells damaged during cell isolation, or cells with too few counts to be analyzed. Click here for more information on Single cell QA/QC. We will not perform Single cell QA/QC in this tutorial; this task would be invoked from the Single cell counts node and the Filter features task discussed below would be invoked from this output node (Filtered counts).
Filter FeaturesFeatures
- Click the Filtering drop-down in the toolbox
- Click the Filter Features task
- Choose Noise reduction
- Exclude features where value <= 0.0 in at least 99.0% of the cells
- Click Finish
Remove gene expression counts that are zero in the majority of the cells.
A task node, Filtered counts, is produced. Initially, the node will be semi-transparent to indicate that it has been queued, but not completed. A progress bar will appear on the Filter features task node to indicate that the task is running.
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