Thanks, Clément Frainay. I know igraph but I have the same confusion with you that is this the co-expression network? Many papers said use pearson correlation to construct such network, but no detail how to perform. As for me, I want to construct co-expression only for differential expression genes and find hub genes(However I don't know such analysis pipeline is suitable or not). I know we can construct networks and find hub genes use gene list and string, but that is PPI, not co-expression network.
How to construct co-expression network with correlation matrix?
Hello, I know how to calculate pearson correlation matrix, but don't know how to construct co-expression network from it. Also shall I filter correlation matrix according each P value? Thanks!
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Arindam Ghosh
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MatthewP
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Refer to Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data. The section 3.12 Calculating Correlation of Gene Expression for Every Pair of Genes explains the steps.
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Arindam Ghosh
I don't know much about co-expression networks, but maybe this can helps you : https://medium.com/@JavierBurroni/visualising-correlations-using-graph-2169c6415427
You can build a network with the igraph library (available python or R), from an adjacency matrix obtained by simply applying a threshold on your correlation matrix.
However you obtain a correlation network, not sure if this is enough to call this a co-expression network
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Clément Frainay
Ok. If you want to compare two conditions, maybe you want to look at differential networks? Not sure if it helps, but here is an example with detailed computation procedure : https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-95
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Clément Frainay
Hey Matthew, you mentioned my tutorial. Please let me know if you have issues in running it. I believe I show how to determine hub genes in the tutorial.
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Kevin Blighe
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