How to create a series report to explore cell populations across experiments
Prior to working with a series report, ensure that you have set up your library and created a series. Learn more about setting up your library here.
Cell Ranger Filter Counts Matrix are the required inputs for the scRNA series report. This zipped file must include the following; barcodes.tsv.gz , features.tsv.gz, matrix.mtx.gz.
Seurat package v4.1.0 and OnClass v1.2 are used to generate the contrasts.
Upload the zipped filter count matrix to the library for each experiment included in the Series or run the first step of a Single Cell Guided Analysis to generate the sample gene count files on the platform.
Once your Series has been created with the appropriate files follow the subsequent steps to create your Series Report.
Step 1. Create a series report. Go to your workspace and select the "Series Report" tab. Create a new series report- provide a name, description, select a series and the BioBox scRNA Dashboard
Step 2. Create a contrast. A contrast will enable you to compare cell populations across experiments. This will generate the data to be used in the UMAP, Cell Quantities, Expression Plots and Differential Expression Widgets.
Provide a name, specify the species, and select "Single Cell RNAseq" for the experiment type. Once "Single Cell RNAseq" has been selected you will be prompted to specify the number of groups that are being compared.
Name each group and select Record or Experiment properties from your Library to subset your experiments. For example, you may have a series of 15 experiments from breast cancer patients and you would like to create a contrast comparing cell populations across patients with the WNT mutation compared to your Normal patients. You can add as many properties as you like to narrow down your experiments
On the following page you will see a list of experiments that match your filter criteria. If any of your experiments have more than 1 filter count matrix file, you will be prompted to select the file to be used in this contrast. Use the checkbox to select the file you would like to move forward with.
This contrast will take a few hours to be generated. The status of the contrast can monitored on the "Data Tab". Once the contrast is complete you can explore your data in the Series Report.
Navigating your series report
UMAP Widget
To enable this widget select "paint data", this will load the UMAP plot. Select a contrast and by default you will see the cell populations annotated with OnClass.
Using the "Annotation Tool" drop down you can swap between the Onclass cell populations or the Seurat Clusters.
Using the "Grouping" drop down you can view the data grouped by Cell Type, Group, or Experiment.
"Explore Data" will enable you to further customize the UMAP plot. Any customizations that you make will be saved to your widget and thus visible on the dashboard overview.
The plot can be customized using the right hand side panel. Under Series you can customize the colours associated with each cell type. The X and Y axis can be customized under the Axis tab. The plot title can be updated under the Grid tab.
The data used to generate the UMAP can be seen under the data tab.
Cell Quantity Widget
This widget enables you to identify the quantities of each population of cells across all of your experiments.
The "Grouping" drop down will enable you to swap between "Split by member" to display cell populations across the groups you are comparing or "All Cells" to view cell populations irrespective of the group they belong to.
The "Value" drop down will enable you to view the number of cells or the percentage of cells.
The "Cell Type Annotation" drop down will enable you to swap between Seurat cluster and Onclass Cell Type groupings.
The "Contrast" drop down will enable you to swap between any contrasts you have generated in this series
Hovering over any of the bars will display the corresponding cell quantity data. Use the zoom sliders located to the right and bottom of the plot to zoom in to specific cell populations.
"Explore data" will take you to a full view of the plot where the axis and plot titles can be customized.
Expression Plot Widget
This widget enables you to explore average expression values across cell populations between the groups you are comparing.
The "Gene" dropdown will allow you to search for a specific gene.
The "Cell Type Annotation" dropdown will allow you to swap between Onclass Cell Type and Seurat cluster annotations
The "Contrast" dropdown will allow you to swap between any contrasts you have generated within their series report.
"Explore data" will take you to a full view of the plot where the axis and plot titles can be customized.
Single Cell Differential Expression Widget
This widget enables you to explore differentially expressed genes within a cell population across the groups you are comparing.
To enable this widget, go to "Explore data" and navigate to the plot tab, this will open the full version of the plot. Select a contrast and the cell type you would like to explore.
Using the right hand plot customization panel, specify the data you would like displayed in the plot. Select the Series, under the X axis select average log2 fold change and under the Y axis select P adjusted value. The average log2 fold change will show the differences in fold change between the two groups you are comparing.
Add tooltips to the plot under the Series tab to display metadata as you hover over data points within the plot.
Under the plot customization Axis tab you can provide titles for your X and Y Axis.
All data displayed in the plot can be accessed and filtered under the "data tab" Use the drop down arrows next to each column header to filter the data on values such as average log2 fold change and p adjusted value.
Use the Insights tab to explore genes and pathways from EnrichR, KEGG, and Reactome that are enriched in your data. Any filters that you apply to the data table will be used to subset your gene list and generate the insights.
Select a pathway to explore the genes enriched in the selected pathway and within your dataset.
All changes that you make to the plot will be saved to the widget and reflected on the series report overview.