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• Click on  Filtering > Filter features from the menu on the right.
• Select Metadata and set the task settings as follows
• Click Finish

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• Click on the resulting filtered counts node and select 
• Select QA/QC > Single cell QA/QC from toolbox,   once the task has completed we can open the report by double-clicking the node:

We will remove the cells with low counts and number of detected features.

• Click on Select & Filter and set lower threshold to 50 for both (remember that this is data-dependent and will change based on your dataset). Then click Image Removed and
• Click FilterImage Added include
• Click Apply observation filter to the filtered counts node:

Click on the node generated by the filtering task

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in the Analyses tab.

• Click Filtering > Filter features. Apply a noise reduction filter:

We can now normalize our filtered data.

• Click Normalization and scaling > Normalization. Use the recommended settings by clicking :

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• Click on the normalized data node, then from
• From the menu on the right select Exploratory analysis > PCA. We are going to use the top 2000 features by variance and calculate the first 50 principal components (PCs):

Once the PCA has run, click on the

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PCA result node in the Analyses tab.

• Select Exploratory analysis > UMAP from the toolbox.Set  Set the UMAP parameters as follows:
  • Top 20 PCs
  • Local neighborhood size 60
  • Minimal distance 0.20

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