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@Camila-goclowski
Camila-goclowski committed Nov 2, 2023
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Expand Up @@ -8,7 +8,7 @@ Multiomic analyses are a new and exciting way to understand the world of biology
Seurat has kept up to date with the capacities of multimodal technologies such as Cite-Seq, which means once you've familiarized yourself with Seurat, you can seamlessly continue to use the package to analyze and explore many other types multimodal single-cell datasets.

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>Check out [Filter, Plot, and Explore with Seurat]({ % link ../../topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md %}) to start doing so in RStudio with an scRNA-seq dataset!
>Check out [Filter, Plot, and Explore with Seurat]({% link ../../topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md %}) to start doing so in RStudio with an scRNA-seq dataset!

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The linked file (`../../topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md`) could not be found.

Raw Output:
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{: .comment}

Before we can start exploring, we'll process our transcriptomic and surface protein measurements into a Seurat object. The hardworking Galaxy programmers have kindly optimized the Seurat tool to include Cite-Seq functionality. This enables the tool to take our raw csv files as input and output Seurat objects which are easy to explore!
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