Tutorial
Content
Xenium interface (NEW)
A short introduction to the new Xenium interface, using a breast cancer sample.
Visium data
Database tab
The database tab provides a table of all samples in DeepSpaceDB. The table can be searched using keywords or using filters on the right side. Clicking on a sample will show a short preview, including the image and details about the source of the sample. To get more detailed sample information, click on the "Sample Page" button.
Sample page
The sample page provides detailed information about each sample, including metadata, quality indicators, image annotations, spatially variable genes, predicted cell types, and an interactive Tissue Explorer tool.
Tissue Explorer: within-sample intereactive analysis
The sample page includes the Tissue Explorer tool. Users can interactively select several parts of a tissue and compare the gene expression patterns between them. The video below illustrates this using a breast cancer sample.
Tissue Explorer: comparison between two samples
On the Database tab, users can select 2 samples to compare between. The Tissue Explorer tool can be used to interactively select parts of different tissue slices and compare between them. The video below introduces this tool using the example of 2 mouse brain samples; a control one and an Alzheimer's disease model brain.
Search using gene or pathway of interest
Tutorial video coming soon!
Upload and explore your own data
On the Upload tab, users can upload, process, and explore their own Visium data. This tool will be made public soon.
Frequently Asked Questions
What are the units of gene expression levels shown in plots?
In the "Spatially variable genes" section of each sample, users can visualize gene expression patterns within the tissue slice (the plot on the right hand side in the figure below). The units shown reflect the normalized gene expression levels in each spot, as calculated by the Seurat R package, function NormalizeData (see here). Briefly, read counts for each gene in a spot are divided by the total read count for that spot and multiplied by a scale factor (default: 10,000). Then, 1 is added to the result, and the natural logarithm is applied (log1p), to avoid issues with log(0).
What are the units of pathway activities shown in plots?
In the "Spatially variable pathways" section of each sample, users can visualize the estimated activity of various pathways within the tissue slice (the plot on the right hand side in the figure below). These activities were calculated using the AddModuleScore function of the Seurat R package (see here). Conceptually, module scores are calculated as follows: the average expression of a set of genes (e.g., genes involved in a given pathway) in each spot is computed, and the average expression of a control gene set is subtracted from it. Positive scores indicate higher-than-expected activity; negative scores indicate lower-than-expected activity.
