(c) Lars Velten Steinmetz lab, EMBL Heidelberg - Launch tutorial - Load default gating scheme: Individual 1

Welcome to the indeXplorer tutorial.
This tutorial will show you how to explore single cell transcriptomic data by a few simple mouse clicks. Press Next to continue.

Next Quit

Updating Plots

Gates are created by clicking into the plots. To create a rectangular gate, click once on the upper left corner, and close the gate by a double click in the lower right corner. For a polygonal gate, click on as many points as you wish and close the gate by double-clicking. To modify an existing gate, type the name of the gate you want to replace and draw it anew.
To store a state, click the button and remember the stateID that will be created


To restore a state, paste an exisiting stateID into the field below and click the button of your choice. Some useful predefined states:
  • defaultI1 Contains all gates used in transcriptomics analysis, as well as the populations from the hierarchical clustering. Displays plots for individual 1.

Updating Plots

This module performs gene ontology analysis of the genes with the 10% highest/lowest loadings. It may take a moment for the results to appear.
To create a gene list, select the number of genes to store and the principle component to use


This is an interface to the MAST package described by Finak et al ( pubmed ) which allows you to identify genes with differenial expression among arbitrary cell populations.

Computations take between one and 10 minutes depending on the number of cells to be analyzed.

Updating Plots

Display options

Changing these values changes the display, without re-running the analysis.

Further analysis

You can create a gene list from all genes that are displayed as significant in the plot. Gene lists can be further analyzed in the Gene lists panel You can perform a Gene Ontology enrichment on the genes that are displayed as significant.

Gene lists are created whenever you perform an analysis. You can also import gene lists through file upload, from Gene Ontology or from select literature resources.

You can use Gene Lists to plot mean expression on scatter plots, to create heat maps, to run clustering algorithms or PCA only on some genes etc.

Download Genelist