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Yes, click on the link "Import a pipeline" on the bottom of the “Analyses” tab dashboard. This will help you import either our hosted pipelines or your own saved pipeline which can be found under Settings -> Components -> Pipelines. Click here for steps to save and run a pipeline. For more information related to navigating pipelines click here. 

How do I classify cells?

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. 

My server is full, how do I make more space?

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Find the reference genome and annotation files for the species of interest using Ensembl. When adding an assembly, we will need both the reference genome and the transcriptome information library files. For more details on adding a reference genome please click here. The annotation file will give us information on gene (transcript) location and we recommend using the .gtf file format; for more information click here. There is no need to unzip or save these files to your local machine, instead right click and copy the link address. We also have a short video here: Library File Management - Partek® Documentation. 

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Can I add transgenes to my reference files? 

To Yes, to add transgenes (including gfp or related) to the references files, choose an assembly, create the transgene reference, and merge the references together (e.g. combine mm10 with dttomato). This is the same process for the annotation file.

How do I

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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. 

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export data from the result nodes?

Yes, left Left click to select the data node you want to export. In the bottom of the task menu there will be an option to "Download data". 

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