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

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PCA task and data nodes will be generated.

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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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Because the upstream PCA task was performed separately for each sample, the t-SNE task will also be performed separately for each sample. t-SNE task and data nodes will be generated (Figure 5).

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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.

There should be 5,322 glioma cells in total across all 8 samples.  

• The classification name can be edited or deleted (Figure 18). 

With the malignant cells in every sample classified, it is time to save the classifications.

• Click Apply classifications in the Classification card on the right
• Click the Filtered counts data node as input data for the classification task (Figure 18)
• Click Select

• Classify icon
• Name the classification attribute Cell type (sample level)
• Click Run (Figure 19)
• Click Run
• Click OK on the information box that says a classification task has been enqueued

Numbered figure captions
SubtitleText Name the cell-level attribute AnchorName Classification Classifiy attribute name
Image RemovedImage Added

A new task, Classify, is added to the Analyses tab. This task produces a new Classify result data node (Figure 20).The new attribute is stored in the Data tab and is available to any node in the project.

• Click on the Glioma (multi-sample) project name at the top to go back to the Analyses tab
• Your browser may warn you that any unsaved changes to the data viewer session will be lost. Ignore this message and proceed to the Analyses tab

• Double-click the new Classify result data node to open the task report (Figure 21)

The Classification summary table shows a breakdown of the number of glioma cells that were classified per sample. The cells that were not classified are labeled N/A.

The Top marker features per label table shows the top 10 upregulated genes in each cell type. In this case, the glioma cells are compared to the N/A cells using ANOVA and the genes are filtered for fold-change >1.5 and sorted by descending fold-change values. To obtain the full list of biomarker genes with p-values and fold-changes, click the Download link in the bottom right of the table.

One multi-sample t-SNE plot

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The PCA task will run as a new green layer.

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Once the task has completed, we can view the plot.

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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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A new task, Classify, is added to the Analyses tab. This task produces a new Classify result data node in a green layer (Figure 32).The new attribute is now available for downstream analysis.

• Click on the Glioma (multi-sample) project name at the top to go back to the Analyses tab
• Your browser may warn you that any unsaved changes to the data viewer session will be lost. Ignore this message and proceed to the Analyses tab

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