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Frequently Asked Questions

In our most recent release, we’ve added new methods, and significantly restructured and improved our codebase. We outline the most significant changes below, particularly for users who have extensive experience with Seurat or want to learn more about the details of the Seurat object.

For new users, especially those getting started with analyzing scRNA-seq data, we suggest working through our guided tutorial of a 2,700 PBMC scRNA-seq dataset from 10X genomics.

1. What new methods are included in Seurat v3.0?

2. I’m used to Seurat v2!

We believe that Seurat v3 offers substantial improvements in both functionality and user-experience, and are committed to making this transition as smooth as possible. We have been particularly careful to ensure that users who have started projects in Seurat v2 can complete existing work prior to upgrading:

3. What manuscripts should I cite if I use Seurat?

If you use Seurat in your research, please consider citing:

In addition, if you use the sctransform workflow, please consider citing:

4. I’ve run an integration analysis and/or sctransform and now want to perform a differential expression analysis. Which Assay should I use?

We recommend running your differential expression tests on the “unintegrated” data. By default this is stored in the “RNA” Assay. There are several reasons for this.

  1. The integration procedure inherently introduces dependencies between data points. This violates the assumptions of the statistical tests used for differential expression.

  2. DE and integration are not currently supported with sctransform but will be soon.

5. How can I find out about more about additional features?