WGCNA for metabolomics?

Analyzing and Reusing Data
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Hi all (metabolomics transcriptomics genomics)

I am new to WGCNA, which was developed for network analyses of gene expression data. Many are now using it for metabolomic data. I haven’t spent much time on this (mental bandwidth occupied elsewhere… sigh) but I am trying to figure it out with a student.

The first hurdle we have encountered is determining the “best” soft power. Based on the Figures below, I think it might be 5 or 8… any advice (anyone or @elahif01 @blehallier @MiaFeng @mcbrumm @jonahkeller @LauraIbanez @Synuclein @jaeyoon.chung )?

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Thanks,
F

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Hey @fbbriggs , thank you for the question! I think it’s always cool to see methods from one domain be applied to another.

Have any of our community members with interest in metabolomic data (@kathrynstep , @MYSchmidt , @mariariverapaz , @NHatcher114 , @jbmchls ) already started applying WGCNA to metabolomic data analyses?

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I have not! Based on just the image @fbbriggs shared, I would choose 5 for the soft threshold.

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Thanks! That was my thought. We are re-working and refining. I will circulate back when I have better clarity.

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