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 Because this data set was already filtered by the study authors to include only high-quality cells, this read counts filter is sufficient for this tutorial. 

• Select Click Apply filter 

A new task, Filter cells, is added to the Analyses tab. This task produces a new Single cell data node (Figure 19).

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A common task in bulk and single-cell RNA-Seq analysis is to filter the data to include only informative genes. Because there is no gold standard for what makes a gene informative or not and ideal gene filtering criterea depend on your experimental design and research question, Partek Flow has a wide variety of flexible filtering options. 

• Click the Single cell data node produced by the Filter cells task
• Click Filtering in the task menu
• Click Filter features (Figure 20)

There are three categories of filter available - Noise reduction filters, Statitics bsaed filters, and Feature list filters (Figure 21).

The Noise reduction filter allows you to exclude genes considered background noise based on a variety of criteria. The Statistics based filters are useful for focusing on a certain number or percentile of genes based on a variety of metrics, such as variance. The Feature list filter allows you to filter your data set to include or exclude particular genes.

We will use a Noise reduction filter to exclude genes that are not expresed by any cell in the data set, but were included in the matrix file.