After running an analysis, you will be able to visual the clusters of cells on a UMAP scatter plot, search for features, visualize the expression of genes in various types of plots and conduct further analyses, such as differential gene expression and pseudotime analysis on your dataset.

Welcome to the explorer page

Here we have an overview of the explorer page and the list of tools and features. You can find links to separate pages with details for some of the more extensive tools here as well.

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UMAP scatter plot

At the very centre of the explorer page is the scatter plot of UMAP_1 and UMAP_2 by default after you have run an analysis. Here you can visual the clustering of cells in your dataset, select cells and annotate the clusters, and so on. You can also change the UMAP to t-sne or view imported coordinates here as well.

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Metrics

You can select to view some of the metrics that can be useful for quality checks on your dataset:

• Transcripts per cell
• Genes per cell
• % of mitochondrial counts
• % of ribosomal counts
• Cell cycling phase scores

💡Tip

You can use the information gathered from the above and reanalyse the dataset again with new parameters. For example, if you find clusters of cells with abnormally high mitochondrial count that’s not relevant to your study, you can choose to reanalyse this dataset and adjust the cell filtering parameters to exclude some of these cells.

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Feature search

You can search for a specific gene or feature in this search bar and conveniently visualise the expression of this gene on the UMAP.

Highly variable genes (HVGs) and other modalities (e.g. ADT) will be labelled here as well when you search for the gene or feature. You can also find and copy gene sets and lists of ADTs or HTOs from CITE-seq data.

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Import/Export data

Import/Export data includes options for:

Import data from csv

Import cell metadata, plot coordinates

Import VDJ annotations

Add clonotypes from VDJ sequencing to your dataset from 10x

Export metadata to csv

Export all metadata from the current analysis to a csv

Export pseudobulk data

Pseudobulk data from different clusters or groups

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Clusters and Groups

On the left of the UMAP, we have the tools and options for clusters, imported cell annotations and cluster markers.

The Group by dropdown contains all cluster information from the analysis run and groups for imported cell annotations can be found here as well.

Cluster markers

These are the marker genes of a cluster, i.e. genes expressed in the cells of this cluster that distinguishes this cluster from the rest. These gene are scored and can be sorted by their marker score, fold change, etc.

If you have specified the species of your dataset during analysis as human or mouse, you will find the MSigDB gene sets for these markers as well.

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Plotting tools

An overview of the plot options you may find on the explorer, you can find the detailed information for different plots on the Visualisation tools page

Gallery

Record of all downloaded plots from this analysis

Bar plot

The bar plot shows the percentage of cells that express a gene or feature across the clusters. You can change the cluster or group values on the x-axis by choosing a different category from Group by.

Violin and Box plots

Visualize how the normalized expression values of a gene or feature is distributed in different clusters/groups. Grid layout options for plotting multiple features/genes are available for both violin and box plots.

Stacked

Visualise cluster composition in a stacked bar plot.

Radar

A radar plot to visualise and compare the expression of multiple sets of genes in clusters or groups.

Dot

A dot plot to visualise the mean expression of genes and the percentage of expression across different clusters.

Scatter

Create a feature scatter plot using two features of interest.

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Analysis tools

Comments

Add a quick note or comment to the dataset

Analysis parameters

Details on the parameters used in the current analysis. This also includes the list of HVGs and blocked genes, and a methodology section which you can copy.

Nygen Insights ✨

Generate auto annotation reports for clusters or groups using AI

Reference mapping

Transfer labels from another dataset

Pseudotime ordering

Create a new pseudotime ordering of cells from selected cell sets

Gene sets

Save and visualise the aggregate expression of sets of genes on the UMAP and other plots

Cell sets & DGE

Create, save and edit selection of cells for differential gene expression (DGE) analysis. Run DGE analysis and view results in tables and volcano plot.

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