Garnett[1] automated cell type classification has been wrapped as the Classification task in Partek Flow. Just like the original Garnett tool, Classification in Flow works on single-cell data, along with a cell type definition (marker) file, and trains a regression-based classifier. Once a classifier is obtained and published, it can be applied to classify future datasets from similar tissues. To improve the user experience, both maker file(.txt) and classifier file(.rds) have been implemented as library files in Flow. 

Flow hosts a few pre-trained classifiers as Managed classifiers. The list of available classifiers can be found here[2]. If a managed classifier exists for your data type, we recommend you try it. Besides the Managed classifiers, the Project classifiers trained on the same dataset prior to your classification can also be used to classify cell type. Project classifiers can be promoted to Managed classifiers if users publish them. 

To classify cell type using a pre-trained classifier:  

Select any non-normalized single cell data node, Filter counts here 

Choose Classify cell type task in Classification section (Figure 1)

Figure 1. Selecting the Classify cell type task.