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How To Build Co-Expression Networks?

Hey guys. I am starting in a new project (in a cooperation between biologists and computer scientists) where we want to build Gene Co-expression Networks from RNA-seq data (in BAM format) to try to identify genes that are expressed together and use this information to classify bees in groups, i.e.: Looking to the networks we see gene 1, 3 and 5 expressed, so this represents an adult Apis mellifera bee. My background is on computer science and I am new to bioinformatics. Could someone recommend to me reproducible research projects (specially with open source code) that use techniques to build Gene Networks? I started looking on Bayesian Networks for this. There are other good techniques being used for co-expression networks? From the point of view of computer science, what are some metrics used to analyse the correctness of resulting networks? On classifiers we use ROC, confusion matrix, what metrics we use to analyse networks? Seems that most of the research papers do a biological analysis of the resulting networks, but I'm missing a computational analysis.

Thanks :)

gene-expression

2 answers

Maybe you want to have a look at Cytoscape. It is capable of calculating and drawing networks using different metrics etc. Also there are presumably tons of add-ons.

This recent paper may be useful.

They use the WGCNA R package.

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