t-SNE is a visualization method commonly used analyze single-cell RNA-Seq data. Each cell is shown as a point on the plot and each cell is positioned so that it is close to cells with similar overall gene expression. When working with multiple samples, a t-SNE plot can be drawn for each sample or all samples can be combined into a single plot. Viewing samples individually is the default in Partek Flow because sample to sample variation and outlier samples can obscure cell type differences if all samples are plotted together. However, as you will see in this tutorial, in some data sets, cell type differences can be visualized even when samples are combined.

Using the t-SNE plot, cells can be classified based on clustering results or differences in gene and pathway expression. 

Plotting samples individually on t-SNE

By default, each sample in a multi-sample data set is plotted on its own t-SNE. 

• Select the Single cell data node
• Select t-SNE from the Visualizations section of the task menu (Figure 1)
  
  

Figure 1. Invoking t-SNE from the task menu

• Select Finish from the t-SNE dialog to run t-SNE with the default settings

A t-SNE task node will be generated (Figure 2).

Figure 2. t-SNE task node

Once the t-SNE task has completed, we can view the t-SNE plot.

• Select the t-SNE task node
• Select Task report from the task menu (Figure 3)

Figure 3. Opening the t-SNE plot

The t-SNE plot will open to the first sample in the data set, Astrocytoma 1 (Figure 4).

Figure 4. Viewing t-SNE plot of Astrocytoma 1

The t-SNE plot is in 3D by default. The 2D t-SNE is also calculated and you can switch between the 2D and 3D plots using the Plot style radio buttons. 

Each sample has its own plot. We can switch between samples using the Back and Next buttons on the upper left. 

• Select Next
  

The t-SNE plot has switched to show the next sample, Astrocytoma 2 (Figure 5). 

Figure 5. Viewing t-SNE plot of Astrocytoma 2

The goal of this experiment is to compare malignant cells from two different glioma subtypes, astrocytoma and oligodendroglioma. To do this, we need to identify which cells are the malignant cells we want to include and which cell are the normal cells we want to exclude. 

The t-SNE plot in Partek Flow offers several options for identifying, selecting, and classifying cells. In this tutorial, we will use expression of known marker genes to identify normal cells. 

To visualize expression of a marker gene, we can color cells on the t-SNE plot by their expression level. 

• Open the Color by drop-down menu
• Select Gene expression from the drop-down menu (Figure 6)
  
  

Figure 6. Selecting color by gene expression

The cells will turn black and a text box Gene ID will open below the drop-down box. 

• Type CD14in the Gene ID text box
• Select CD14 from the list of genes in the data set (Figure 7)
  
  

Figure 7. Coloring cells by CD14 expression

The cells will be colored from black to green based on their expression level of CD14, with cells expression higher levels being more green (Figure 8).

Figure 8. Cells colored by CD14 expression

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