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The Hashtag demultiplexing task is an implementation of the algorithm used in Stoeckius et al. 2018¹ for multiplexing cell hashing data. The task adds cell-level attributes "Sample of origin" and "Cells in droplet".  

Prerequisites for running Hashtag demultiplexing

To run Hashtag demultiplexing, your data must meet the following criteria:

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If you want to specify each Sample of origin instead of using the hashtag feature ID, you will need to prepare a Sample ID .csv file with the hashtag feature ID in the first column and the corresponding sample ID in the second column. 

Running Hashtag demultiplexing

• Click the Normalized counts data node for your cell hashing data
• Click Hashtag demultiplexing in the Pre-analysis tools section of the toolbox
• Click Browse to select your Sample ID file (Optional)
• Click Finish to run

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It is also possible to use the Merge matrices task to combine your data types and attributes. 

References

Stoeckius, M., Zheng, S., Houck-Loomis, B., Hao, S., Yeung, B.Z., Mauck, W.M., Smibert, P. and Satija, R., 2018. Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics. Genome biology, 19(1), p.224.

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