microbetag on Cytoscape

microbetag web-app v1.0.1 MGG v1.0.0

CytoscapeApp Tutorial files

Note

INPUT FILES AND PARAMETERS SETTING

Please, download the files required for the different cases and set the parameters as shown in this tutorial. Parameters are essential especially for the online version of microbetag as they can lead either to non-optimal annotations or even failures of the software. You may check the FAQs section for rules of thumb on how to set your parameters and you are always welcome to join us on Matrix and ask us directly.

We show how to install and use the microbetag Cytoscape app (called MGG) and use it with your data to get microbetag-annotated networks using the microbetagDB and the online version of microbetag. We also highlight the MGG features that allow you to go through the nodes and the edges annotations returned.

From the main menu box, you will have access to all features of the app. As you see, the Get Annotated Network is currently not a clickable option. That is because microbetag has no input yet.

You need first to feed the app with your abundance table and, if available, your co-occurrence network. In both cases though, the abundance table will be required.

Please, make sure your taxonomy fits the criteria for microbetag to run. You may find more on that issue on the Input files section.

Then, as you will see in the following two cases, you will have to set the values to a set of parameters to describe your input data but also what annotation steps you would like microbetag to perform.

Parameter	Variable	Description	Value
Choose input type	input_category	In case you already have a network, set it as network and load it; otherwise set it as abundance_table. In both cases you need to provide the abundance table though	[abundance_table | network]
Choose taxonomy database	taxonomy	In case a user’s taxonomy is to be used, denotes which taxonomy scheme to be used from microbetag	[GTDB | dada2 | qiime2]
phenDB annotations	phenDB	return phenotypic traits based on phen models	bool
FAPROTAX annotations	faprotax	return annotations using the FAPROTAX database	bool
Pathway Complementarity	pathway_complement	return pathway complementarities between associated nodes	bool
Seed scores and complements	seed_scores	return complementarity and cooperation scores based on metabolic reconstructions seed sets	bool
Network clustering	manta	return clusters of nodes on the network using the manta package	bool
Consider children taxa	get_children	use genomes of children taxa of the taxa in the abundance table based on the NCBI Taxonomy scheme, relevant only if you use Other taxonomy	bool
heterogeneous	heterogeneous	(FlashWeave) enable heterogeneous mode for multi-habitat or -protocol data with at least thousands of samples (FlashWeaveHE)	bool
sensitive	sensitive	(FlashWeave) enable fine-grained associations (FlashWeave-S, FlashWeaveHE-S), sensitive=false results in the fast modes FlashWeave-F or FlashWeaveHE-F	bool

The column Variables in the above table provides the variable names you need to use in case you are about to use microbetag from Python (see tutorial).

The datasets to be used in all cases except of the Using a network tutorial, are subsets of abundance tables with no special biological meaning. However, in the Using a network case, we do use the network of Hessler et al. (2023) who we would like to thank for sharing their data.

Tutorials

• .. using an abundance table
• .. using an abundance table and a metadata file
• .. using a co-occurrence network
• Load networks to Cytoscape and microbetag
  • Load an edge list to be used with microbetag
  • Load edge list coming from the microbetag preparation step
  • Load already microbetag-annotated networks!