Skipping the clustering
Dear all, I already know my data clustering affected by my batches and I read thatI can skip the clustering part in the training but I am not sure how this is achieved! should I just skip the FlowSOM.params in the training function and then the clustering is skipped? sorry but this was't so clear to me in the documentation. Also I have a question regarding to the training data. Can the training data be used with normalized facs files or do I need to normalize the training data too by somehow including them in the normalization process?
Thank you so much!
Hello, I also cannot find in the documentation how to skip the clustering step and would like to know how to achieve this.
Hi all,
If you don't want to include the clustering step, you can use the QuantileNorm.train and QuantileNorm.normalize functions from the CytoNorm package. The CytoNorm.train/normalize functions are actually wrappers around those to apply it on clusters.
Hope this helps! Sofie
On Tue, 27 Jun 2023, 15:40 Hefin Ioan Rhys, @.***> wrote:
Hello, I also cannot find in the documentation how to skip the clustering step and would like to know how to achieve this.
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Thank you @SofieVG , that makes sense. Thank you again for contributing such impactful packages to the field!