CytoNorm allows for batch normalization, using batch controls, to address batch effects and is available as a task in OMIQ. Batch effects are considered to be non-biological variation between groups of samples.
Van Gassen, S., Gaudilliere, B., Angst, M.S., et al. CytoNorm: A Normalization Algorithm for Cytometry Data. Cytometry, 97: 268-278. https://doi.org/10.1002/cyto.a.23904
1. Prepare your Data
1.1 Add Metadata to your Dataset
Batch and control metadata are required to run CytoNorm. Batch metadata is normally represented by whole numbers where each number denotes a particular batch; same numbers denote files belonging to the same batch. Control metadata denotes which files are control files and which are sample files.
To learn more about how to add metadata to your dataset, please view Setting your Metadata.
1.2 Perform any Compensation/Unmixing and Scaling Tasks
Prepare your data as you usually would for flow cytometry analysis. Find links to useful resources below:
1.3 Perform Cleanup Gating and Subsampling Tasks
It is recommended to perform cleanup gating and subsampling to exclude debris, doublets, dead cells, etc from the normalization task. Debris, doublets, dead cells, etc can lead to a sub-optimal CytoNorm normalization.
To learn more about performing gating and subsampling, please see our How to Perform Gating and Subsampling resource page.
1.4 Perform a Clustering Task
CytoNorm needs a Cluster Member Feature for the task to run. In this example, we have used FlowSOM to generate the clusters, but you can use other clustering tasks.
Find information on how to perform a clustering task here.
2. Add CytoNorm Task to your Workflow
Click Add new child task and select CytoNorm from the task selector. In this example, we are using Files that are already compensated and therefore have not included a compensation task. We have chosen to perform FlowSOM clustering
Your exact workflow branch may look different than the example above, depending on Steps (1.2), (1.3), and (1.4). The important thing is that your workflow follows a logical ordering of tasks.
3. Setup and Run CytoNorm
3.1 Select Files and Features
Select the Files you want to correct for batch effects. Include your control files in the selection. Select the Features you want to include. Note that the physical parameters and auto-fluorescence (if applicable) are not included. Do not include any clustering features that will show in the list.
3.2 Enter CytoNorm Settings
Number of Quantiles: Describes the distribution of the markers and correlates with the spline function for normalization
Batch Metadata Field: Add the metadata pertaining to the batch membership of the samples here as entered in Step (1.1) here. This does not need to be called batch.
Control Metadata Field: Add the metadata identifying the control files and sample files here as entered in Step (1.1) here. This does not need to be called Control.
Cluster Membership Feature: Add the result of the clustering task here.
Batch for Target Distribution (Optional): If you want to normalize using a particular batch number, input it in here.
3.3 Run
Click Run CytoNorm. This will take you to the Status tab and you can watch the progress. However, you are free to go back to your workflow or do whatever you please while this runs in the cloud. The status can also be seen in the Workflow itself, or you can have an email sent to you when it is completed.
4. Review your Results
Go to the Results tab to review your Results. Here I have chosen to download the CytoNorm _cluster_plots.zip to view how CytoNorm have normalized the data on the control files.
5. Continue to Build your Workflow
If you are satisfied with the batch normalization results then you can simply continue to build this workflow branch and the normalized Features will be available in downstream tasks.
Useful Tip: Change Channels to Reflect Normalized Values
You can change the feature channels to reflect the normalized values.
Go the the Results Tab. In the Results Columns, open the Rename Result Columns.
Type -Norm in the Find text box. Type a "space" in the Replace text box. Click Configure Names.
Select all Result Columns. Click Submit.
Check the New Name column that "-Norm" has been deleted. Click Submit.
The features downstream of the CytoNorm task will now only contain the normalized features.