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Classification in Partek Flow can be performed manually or with automatic cell classification which is explained in more detail here. Users often want to classify cells by gene expression threshold(s), for details on classification by marker expression click here. Automatic classification needs to be performed on a non-normalized single cell data node; once complete, publish cell attributes to project then use this classification in visualizations and tasks. You may choose to perform Graph-based clustering and K-means clustering to help identify biomarkers that can then be used to identify the clusters and we also provide hosted lists for different cell types. 

Can I visualize fold change values on a heatmap without using a z-score?

Yes, the default settings can be modified by clicking "Configure" in the Advanced settings during task set-up, then change the "feature scaling" option to "none" to plot the values without scaling. For more information related to to the heatmap click here. 

Statistics FAQs

Why do I get "?" for FDR p-values in my Deseq2 result?

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