Frequently Asked Questions

How can I learn to use ImmuNet to address the specific question I have?

Go through the tutorials available on the site. Read the publication for use examples.

I’m still lost. I have a question about ImmuNet and cannot find the answer in the documentation.

Please contact

I was using ImmuNet and got a strange error warning. What do I do?

Please send information on exactly what you were doing, your browser (and version), and operating system, include a screenshot if possible to

Why don’t I see any connections to the seed genes I used to create a network?

The visualization prioritizes which connections to display. You can adjust the network filter slider to show lower confidence connections.

The display shows disconnected graphs and connections to the node I am most interested in are not shown. What do you suggest?

You can adjust the Network Filter slider to increase the number of connections shown. This will show lower confidence relationships. If the relationships to your node of interest are still very low, you may want to try your query using another network.

How are the genes selected to be shown?

One would expect that the N (default N=15) interactions with the highest weight would be presented, but this is not the case. Genes are normalized against their overall connections throughout the network for choosing which to display. Hyper-connected genes are thus down-weighted which reduces the chances of hairball graphs.

Can I download a network trained on one of the non-immune KEGG pathways?

Yes. Please contact This is not available by default to keep the site easy to use and because these networks are very large files.

How do I decide which ImmuNet network to use for making predictions?

Try to choose the network that is most appropriate for the area of inquiry. If you are not sure, you can use the human global immune network or you can try several of the specific networks and explore the results.

Do the connections shown come from both the training set (known connections) and the data compendium?

All connections are inferred from the data compendium. The known connections are used to train the network, but if any “known” connections are not supported by the data, they will have extremely low weights and will not be displayed.

How do I find out the weighting of the different data sets for a predicted connection?

If you click on the edge of the network, you can see the evidence used and relative weight for making each edge prediction.

How do you handle overlapping data in the underlying compendium? Doesn’t some data being more abundant drown out the other data?

The Bayesian integration methods utilized handle these issues automatically by weighing all underlying data according to how useful they are for making predictions in the training set. All data of any type that improves prediction is utilized and weighed accordingly. In the example shown in Table S2 in the paper, for example, many types of data are highly weighted in making inferences. This is what is typically found. We have found no evidence that any type of data drowns out any other type of data in making predictions.

How do I download the ImmuNet networks for my analysis?

The ImmuNet networks are available for download as tab-delimited, gzipped files here. These networks include all edges with a posterior probability above the prior(0.005). They are presented in the following format:

[Entrez GeneID 1] [Entrez GeneID 2] [Posterior Probability]

Once the files are uncompressed they may be opened as tab delimited files with Excel or a text editor. Due to the large size of these network files we recommend using the ImmuNet interface for any network visualization.

How do I cite ImmuNet?

Gorenshteyn D, Zaslavsky E, Fribourg M, Park C, Wong AK, Tadych A, Hartmann BM, Albrecht RA, Garcia-Sastre A, Kleinstein SH, Troyanskaya OG, Sealfon SC. Investigating immunological pathways and diseases with a comprehensive compendium of human data. Immunity. 2015