I'm wondering if there is a clear method that can be used to create the bipartite network to connect the samples with OTUs/taxa. As I searched the internet, all of the tutorials are talking about how to plot it but not how to calculate or how to get the associations between samples and taxa. Also, the papers that used bipartite network are unclear about the methods either. Although the qiime have the function to get the nodes and edges for bipartite (http://qiime.org/scripts/make_bipartite_network.html), it is unclear how qiime does the analysis. So what is the method/algorithm behind this?
Hi Haitao,
associations are mostly calculated using correlations. Other metrics are also used like distance, similarities. Based on cut-offs and significance, an edge list can be prepared, and network can be generated.
Follow this link, and go through the full tutorial.
http://psbweb05.psb.ugent.be/conet/
I hope this helps.
Anubhav
Hi Dr. Wang,
if you're looking for a way to generate the actual image given a list of interactions, an R package called "bipartite" has been designed to create the visual outputs. They have good documentation that you should be able to follow: https://cran.r-project.org/web/packages/bipartite/bipartite.pdf.
I have also attached my own use of this package (r script and image output) to depict microRNA:mRNA interactions. It has comments throughout, so you should be able to follow it.
Hello Haitao Wang ,
Have you found some solution about creating such network yet? I have been also trying to make with smaller dataset. I have been trying to create co-occurrence network with CoNet app from Cytoscape but its not working as it should be.
Milan
Hi Haitao,
hope you already solved this issue. If not, I had a similar problem and I wanted to construct a bipartite network of OTUs and Samples in R, to avoid porting data back to QIIME. Searching around I finally found an excellent solution!
So, if it is an R solution you are looking for, I can surely suggest to go through this tutorial https://solomonmg.github.io/blog/2012/Working-with-Bipartite-Affiliation-Network-Data-in-R/. I still need to understand if everything was done correctly as the tutorial was originally made for other type of data, and eventually to explore further functionalities, but it is well explained and get the thing done.
Hope this help,
Francesco.
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