Classification

Classification in Partek Flow

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.

Garnett classifiers 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.

Cell ranger task report in Flow

Task report is sample based. Users can use the dropdown list on the top left to switch samples. Under the sample name, there are two tabs on each report - Summary report and Analysis report (Figure 7). Important information on Estimated Number of Cells, Mean Reads per Cell, Median Genes per Cell, as well as information on Sequencing, Mapping, and Sample are summarized in different panels. The Barcode Rank Plot has also been included as an important piece in the Cells panel in the Summary report (Figure 7).

Figure 7. The example report of Cell ranger task in Flow.

Another two plots -biplots of Sequencing Saturation and Median Genes per Cell to Mean Reads per Cell have been included in the Analysis report as they are important metrics to library complexity and sequencing depth (Figure 8).

Figure 8. Analysis report of Cell ranger task in Flow.

Details will be exhibited and the panel will be expanded correspondingly if the the icon is clicked. In the example below, the plot of Median Genes per Cell has been expanded while the Sequencing Saturation plot hasn't (Figure 9).

Figure 9. Expanded panel of Cell ranger task report in Flow.

Users can click Configure to change the default settings In Advanced options (Figure 5).

Expected cells: Expected number of recovered cells. Default: 3,000 cells.

Force cells: Force pipeline to use this number of cells, bypassing the cell detection algorithm. Use this if the number of cells estimated by Cell Ranger is not consistent with the barcode rank plot.

References

Additional Assistance

If you need additional assistance, please visit our support page to submit a help ticket or find phone numbers for regional support.

Classify cell type

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.

Managed classifiers users will be asked to create a new classifier file if it is the first time to run the task in Flow (Figure 2a). Users could select either Download Garnett classifier that matches the species and tissue type with the dataset working on from Flow maintaining list or Import Garnett classifier that’s trained out of Flow (Figure 2b). Then push the Create button to create the classifier file. Once the right classifier file has been created, Select Finish to start running the task (Figure 2d).

Figure 2. Create Garnett classifier from Managed classifiers and run Classify cell type task with the selected classifier.

Partek Flow Documentation

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