QA/QC & Data Processing

Image RemovedImage Added

Once the data has been imported in the project we can start pre-processing the data:

We will first remove all non-expression features in the data (

...

e.g. NegProbes).

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

Image Modified

In the Analyses tab

• 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-depended 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:

Image Modified

Click on the node generated by the filtering task

...

in the Analyses tab.

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

Image Modified

We can now

...

normalize our filtered data.

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

Image Modified

Data Exploration

Now that we have filtered low quality cells and normalised normalized our data, we can start clustering to identify cell populations.

• Click on the normalised 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):

Image Modified 

Once the PCA has run, click on the

...

PCA result node in the Analyses tab.

• Select Exploratory analysis > UMAP from the toolbox.Run  Set the UMAP parameters as defaultfollows:

  ...

  • • Top 20 PCs
    • Local neighborhood size 60
    • Minimal distance 0.20

   Image Added

  
  

  While the UMAP is running we can also queue a clustering

  ...

  task. Select Exploratory analysis > Graph-based clustering. 

  • We are going to use the Leiden algorithm to cluster our data . (make sure to select the radio button for it)
  • Set the number of PCs to 10 
  • In the advanced settings, set the resolution parameter to 1e8e-4 5 and click Apply:

  Image RemovedImage Added

  
  

  
  

  
  

  
  

  
  

  Page Turner
  button-links true

  ...