> For the complete documentation index, see [llms.txt](https://help.bioinsight.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.bioinsight.illumina.com/dragen-stratamap/temporary.md). # Temporary ScType (native) documentation #### ScType ScType is "a fully-automated and ultra-fast cell-type identification based solely on a given scRNA-seq data, along with a comprehensive cell marker database as background information."\[2]. It allows accurate cell typing in scRNAseq and spatial transcriptome data \[3]. The task can be called from any non-normalised counts node, in the *Classification* menu on the right. * Click on the Counts node. * Click on *Classification> ScType cell classification* in the toolbox. * Select the marker database from the drop-down, the original ScType database is provided by default. * Use the checkboxes to the select the appropriate tissues. * The task uses an existing attribute for the classification, select the node and the attribute from the drop-down, by default a Leiden clustering node will be selected (if it exists). * Select the significance threshold in the *Advanced options*. This number indicates the fraction of cells, higher numbers indicate a less strict significance threshold (see paper for method details). * The task allows for selection of positive and/or negative biomarkers, in the *Advanced options.* * Click **Finish** to run the task.

ScType task setup

The task outputs an annotation for each cell in the dataset. If a cell does not pass the significance threshold it will be classified as N/A. The annotation is saved as 'sctype', and is available from the node. You can use *Annotation/Metadata>Publish cell attributes to project* in the toolbox to make the attribute available at the Analysis level. **References** \[2] Ianevski, A., Giri, A. K., & Aittokallio, T. (2022). Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data. Nature communications, 13(1), 1246. \[3] Nader, K., Tasci, M., Ianevski, A., Erickson, A., Verschuren, E. W., Aittokallio, T., & Miihkinen, M. (2024). ScType enables fast and accurate cell type identification from spatial transcriptomics data. Bioinformatics, 40(7), btae426. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://help.bioinsight.illumina.com/dragen-stratamap/temporary.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.