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fogellab / multiWGCNA

an R package for deep mining gene co-expression networks in multi-trait expression data
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using multiWGCNA for metabolomics data #2

Closed yashwantkumar closed 11 months ago

yashwantkumar commented 12 months ago

I have case control experiment in which multiple tissue metabolomics has been done. We are interested in identifying disease specific metabolic network change in different tissue as compare to their control. We could run the complete pipeline given but we are getting modules that is common in combined, disease and control. Does this mean that there is no module specific to disease?

dariotommasini commented 11 months ago

Hi @yashwantkumar,

Not necessarily. A module might be interesting for two reasons: it has disease-specific preservation (e.g. unique to disease or lost in disease) or disease-specific expression. Thus, there could be a conserved transcriptional network present in both your conditions, but perhaps it was higher/lower expression in disease. You can use the runDME analysis to check for modules that have a significant association with either disease or tissue in your case. The astrocyte vignette might be helpful since it has an identical design.

Let me know if that doesn't work, Dario

smukher2 commented 6 months ago

PLEASE HELP STOP PLAGIARISM AND VILLAINOUS SCIENTISTS BRENT FOGEL (UCLA) AND DARIO TOMMASINI (now PhD student in UC Berkeley) BY NOT CITING OR USING THIS, OR THEIR OTHER CODES AND PAPERS BY THEM. INSTEAD USE AND CITE THE ORIGINAL WORKS (WITH VIDEO TUTORIAL) BY DR. STEVE HORVATH, DR. PETER LANGFELDER AND DR. JEREMY MILLER.(details below)

*For details about wrong doings by Brent Fogel including and not limited to plagiarism by Brent Fogel and Dario Tommasini please see open letter at http://tinyurl.com/bde788x2 or file 'This To Apprise You About Wrong Doings By Brent Fogel including and not limited to plagiarism by Brent Fogel and Dario Tommasini.pdf' posted at https://gitlab.com/smukher2/openletter that I also emailed to UCLA, UC Berkeley, iScience and BMC Bioinformatics reporting plagiarism by Brent Fogel and Dario Tommasini in their two papers using this multiWGCNA code https://github.com/fogellab/multiWGCNA: Tommasini D, Fox R, Ngo KJ, Hinman JD, Fogel BL. Alterations in oligodendrocyte transcriptional networks reveal region-specific vulnerabilities to neurological disease. iScience. 2023 Mar 8;26(4):106358. doi: 10.1016/j.isci.2023.106358. PMID: 36994077; PMCID: PMC10040735. Tommasini D, Fogel BL. multiWGCNA: an R package for deep mining gene co-expression networks in multi-trait expression data. BMC Bioinformatics. 2023 Mar 24;24(1):115. doi: 10.1186/s12859-023-05233-z. PMID: 36964502; PMCID: PMC10039544.

*If you need WGCNA codes for different applications with video turorial consider using the original works (with video tutorials) by Dr. Steve Horvath, Dr. Peter Langfelder and Dr. Jeremy Miller: Langfelder, P., Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008). https://doi.org/10.1186/1471-2105-9-559 Miller JA, Horvath S, Geschwind DH. Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc Natl Acad Sci U S A. 2010 Jul 13;107(28):12698-703. Epub 2010 Jun 25. PMID: 20616000; PMCID: PMC2906579. https://doi.org/10.1073/pnas.0914257107

Video: Dr. Steve Horvath Weighted gene co-expression network analysis https://youtu.be/rRIRMW_RRS4?si=A-ZivIzwdRVLpaLa Video: Dr. Jeremy Miller How WGCNA Can be Used to Compare and Contrast Two Networks https://youtu.be/aBD67YmCBK4?si=eW9Ybv2nIWDUjkdT Full Playlist: WGCNA https://www.youtube.com/playlist?list=PLtlynCnS_vmB2kwhfkcfxIDbsSO9uniM5 Resources: Dr. Peter Langfelder lists further resources on his website https://peterlangfelder.com/2018/11/25/wgcna-resources-on-the-web/

Best regards, Shradha Mukherjee https://gitlab.com/smukher2 https://github.com/smukher2 https://orcid.org/0000-0002-3249-2551 https://pubmed.ncbi.nlm.nih.gov/?term=Shradha+Mukherjee