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• Click Finish to run PCA with default settings (Figure 2)

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• Click Finish from the t-SNE dialog to run t-SNE with the default settings (Figure 4)

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

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The t-SNE plot is in 3D by default. To change the default, click your avatar in the top right > Settings > My Preferences and edit your graphics preferences and change the default scatter plot format from 3D to 2D. 

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

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The cells will be colored from black to green based on their expression level of BCAN, with cells expressing higher levels more green (Figure 9). BCAN is highly expressed in glioma cells. 

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Once cells have been classified, the classification is added to Classify. The number of cells belonging to the classification is listed. In MGH42, there are 460 glioma cells (Figure 15). 

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• Select Classify selection in the Classify icon
• Type Glioma or select Glioma from the drop-down list (Figure 17)
• Click Save

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• Repeat these steps for each of the 6 remaining samples. Remember to go back to the first sample (MGH36) to classify the glioma cells in that samples too.

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• Search for and select green t-SNE data node (Figure 25)

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Using marker genes, BCAN (glioma), CD14 (microglia), and MAG (oligodendrocytes), we can assess whether these multi-sample clusters belong to our known cell types. 

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